def wavyfin(self):
product_master_data = []
master_dict = {}
product_name = 'wavyfin_part'
product_code = 'wavyfin' # PK
product_class = 'N03'
product_num = 'PART2'
product_target_l = 'wavyfin_l_100'
product_target_w = 'wavyfin_w_50'
product_target_h = 'wavyfin_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
MySQL_query.insert_product_master(product_master_data)
return master_dict
def body(self):
product_master_data = []
master_dict = {}
product_name = 'body_part'
product_code = 'body' # PK
product_class = 'N03'
product_num = 'PART1'
product_target_l = 'body_l_200'
product_target_w = 'body_w_100'
product_target_h = 'body_h_50'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
MySQL_query.insert_product_master(product_master_data)
return master_dict
def Pareto():
count_list = []
count_All_list = []
All_list = []
All_pareto_list = []
OP10_NOK = MySQL_query.get_data_for_pareto('OP10')
OP20_NOK = MySQL_query.get_data_for_pareto('OP20')
OP30_NOK = MySQL_query.get_data_for_pareto('OP30')
OP40_NOK = MySQL_query.get_data_for_pareto('OP40')
OP50_NOK = MySQL_query.get_data_for_pareto('OP50')
count_OP10 = OP10_NOK[0]['NOK']
count_OP20 = OP20_NOK[0]['NOK']
count_OP30 = OP30_NOK[0]['NOK']
count_OP40 = OP40_NOK[0]['NOK']
count_OP50 = OP50_NOK[0]['NOK']
count_list.append(count_OP10)
count_list.append(count_OP20)
count_list.append(count_OP30)
count_list.append(count_OP40)
count_list.append(count_OP50)
count_All_list.append(count_list)
count_All_list.append(count_list)
All_list.append(count_All_list)
All_pareto_list.append(All_list)
return jsonify(All_list)
def op30_WIP(self):
master_dict = {}
product_master_data = []
product_name = 'WIP30'
product_code = 'op30_WIP' # PK
product_class = 'N02'
product_num = 'WIP3'
product_target_l = 'op30_l_200'
product_target_w = 'op30_w_180'
product_target_h = 'op30_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
MySQL_query.insert_product_master(product_master_data)
return master_dict
def Search():
if not 'ID' in session:
return ''' <script> location.href = "http://54.180.83.130:5000/" </script> '''
# return ''' <script> location.href = "http://127.0.0.1:5000/" </script> '''
else:
key60 = 'P10001'
product_key = MySQL_query.get_key_product_for_search(key60)
product_key = product_key[0]['product_key']
content_list = Search_data(product_key)
if request.method == 'GET':
key60 = request.args.get('key')
if key60 == None:
key60 = 'P10001'
product_key = MySQL_query.get_key_product_for_search(key60)
product_key = product_key[0]['product_key']
content_list = Search_data(product_key)
## 넘겨받은 값을 원래 페이지로 리다이렉트
html = render_template('Search.html',
data_list=content_list,
key=product_key)
return html
return render_template('Search.html',
data_list=content_list,
key=product_key)
def flange2(self):
product_master_data = []
master_dict = {}
product_name = 'flange2_part'
product_code = 'flange2' # PK
product_class = 'N03'
product_num = 'PART6'
product_target_l = 'flange2_l_30'
product_target_w = 'flange2_w_50'
product_target_h = 'flange2_h_30'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
MySQL_query.insert_product_master(product_master_data)
return master_dict
def Quality_load():
if request.method == 'GET':
char1 = request.args.get('date1')
char2 = request.args.get('date2')
NOK_count_list = []
OK_count_list = []
OP10_NOK_list = MySQL_query.get_data_for_pareto_NOK(
'OP10', char1, char2)
OP20_NOK_list = MySQL_query.get_data_for_pareto_NOK(
'OP20', char1, char2)
OP30_NOK_list = MySQL_query.get_data_for_pareto_NOK(
'OP30', char1, char2)
OP40_NOK_list = MySQL_query.get_data_for_pareto_NOK(
'OP40', char1, char2)
OP50_NOK_list = MySQL_query.get_data_for_pareto_NOK(
'OP50', char1, char2)
NOK_OP10 = OP10_NOK_list[0]['NOK']
NOK_OP20 = OP20_NOK_list[0]['NOK']
NOK_OP30 = OP30_NOK_list[0]['NOK']
NOK_OP40 = OP40_NOK_list[0]['NOK']
NOK_OP50 = OP50_NOK_list[0]['NOK']
OP10_OK_list = MySQL_query.get_data_for_pareto_OK('OP10', char1, char2)
OP20_OK_list = MySQL_query.get_data_for_pareto_OK('OP20', char1, char2)
OP30_OK_list = MySQL_query.get_data_for_pareto_OK('OP30', char1, char2)
OP40_OK_list = MySQL_query.get_data_for_pareto_OK('OP40', char1, char2)
OP50_OK_list = MySQL_query.get_data_for_pareto_OK('OP50', char1, char2)
OK_OP10 = OP10_OK_list[0]['OK']
OK_OP20 = OP20_OK_list[0]['OK']
OK_OP30 = OP30_OK_list[0]['OK']
OK_OP40 = OP40_OK_list[0]['OK']
OK_OP50 = OP50_OK_list[0]['OK']
NOK_count_list.append(NOK_OP10)
NOK_count_list.append(NOK_OP20)
NOK_count_list.append(NOK_OP30)
NOK_count_list.append(NOK_OP40)
NOK_count_list.append(NOK_OP50)
OK_count_list.append(OK_OP10)
OK_count_list.append(OK_OP20)
OK_count_list.append(OK_OP30)
OK_count_list.append(OK_OP40)
OK_count_list.append(OK_OP50)
html = render_template('Quality.html',
quality_OK_list=OK_count_list,
quality_NOK_list=NOK_count_list,
date1=char1,
date2=char2)
return html
def Scatter_OP40():
machine_code = 'OP40'
size_L = 'l'
size_H = 'h'
size_W = 'w'
data_All_list = []
data_L_list = []
data_H_list = []
data_W_list = []
list_L_dict = MySQL_query.get_data_for_scatter(machine_code, size_L)
for i in range(len(list_L_dict)):
temp_L_list = []
x = list_L_dict[i]['machine_data']
y = list_L_dict[i]['product_size']
temp_L_list.append(x)
temp_L_list.append(y)
data_L_list.append(temp_L_list)
list_H_dict = MySQL_query.get_data_for_scatter(machine_code, size_H)
for i in range(len(list_H_dict)):
temp_H_list = []
x = list_H_dict[i]['machine_data']
y = list_H_dict[i]['product_size']
temp_H_list.append(x)
temp_H_list.append(y)
data_H_list.append(temp_H_list)
list_W_dict = MySQL_query.get_data_for_scatter(machine_code, size_W)
for i in range(len(list_W_dict)):
temp_W_list = []
x = list_W_dict[i]['machine_data']
y = list_W_dict[i]['product_size']
temp_W_list.append(x)
temp_W_list.append(y)
data_W_list.append(temp_W_list)
data_All_list.append(data_L_list)
data_All_list.append(data_H_list)
data_All_list.append(data_W_list)
data_All_list_list = []
data_All_list_list.append(data_All_list)
return jsonify(data_All_list_list)
def progress_gauge(self): # 게이지 값 리턴하는 함수
data = MySQL_query.get_item_count_for_gauge()
count_new_product = data[0]['item_count']
get_gauge = (count_new_product / 8640) * 100
return get_gauge
def Productivity_Calculator(self):
data = MySQL_query.get_item_count_for_productivity(1)
total_productivity = (data[0]['total_item_count'] / 8640) * 100
total_productivity = round(total_productivity, 1)
return total_productivity
def op50(self):
machine_master_data = []
master_dict = {}
machine_code = 'OP50' # 설비 코드명
machine_class = 'MCO2' # 용접 조립
machine_process_time = 'exp10'
machine_assembly = 'op40_flange2'
machine_data_code = 'T01'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
MySQL_query.insert_machine_master(machine_master_data)
return master_dict
def op30(self):
machine_master_data = []
master_dict = {}
machine_code = 'OP30' # 설비 코드명
machine_class = 'MCO1' # 단순 조립
machine_process_time = 'exp10'
machine_assembly = 'op20_pipe2'
machine_data_code = 'E01'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
MySQL_query.insert_machine_master(machine_master_data)
return master_dict
def op60(self):
machine_master_data = []
master_dict = {}
machine_code = 'OP60' # 설비 코드명
machine_class = 'MCO3' # 최종 검사
machine_process_time = 'exp10'
machine_assembly = 'final_test'
machine_data_code = 'TEST'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
MySQL_query.insert_machine_master(machine_master_data)
return master_dict
def real_value():
now_data = MySQL_query.get_count_for_progress(1) # 실제값 하루 생산되는 양품수
OK_count = now_data[0]['product_count']
quality = round(OK_count, 1)
data = [(time.time() + 32400) * 1000, quality]
response = make_response(json.dumps(data))
response.content_type = 'application/json'
return response
def EGRC(self): # EGR Cooler 제품
master_dict = {}
product_master_data = []
product_name = 'EGR_Cooler'
product_code = 'EGRC' # PK
product_class = 'N01'
product_num = 'P01'
product_target_l = 'op60_l_260'
product_target_w = 'op60_w_180'
product_target_h = 'op60_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
MySQL_query.insert_product_master(product_master_data)
return master_dict
def Quality_Calculator(self):
data = MySQL_query.get_item_count_for_quality(1)
OK_count = data[0]['item_count']
NOK_count = data[1]['item_count']
if OK_count < NOK_count:
temp = OK_count
OK_count = NOK_count
NOK_count = temp
quality = OK_count / (OK_count + NOK_count) * 100
quality = round(quality, 1)
return quality
def op30(op20):
op30_data = {}
std = 0.0025
product_key = op20[0]
pipe2_l = np.random.normal(30, std)
pipe2_l = round(pipe2_l, 5)
pipe2_w = np.random.normal(50, std)
pipe2_w = round(pipe2_w, 5)
pipe2_h = np.random.normal(30, std)
pipe2_h = round(pipe2_h, 5)
op30_process_time = op20[4]
op30_electricity = np.random.uniform(89.5, 100)
op30_electricity = round(op30_electricity, 5)
op30_data['pipe2_l'] = pipe2_l
op30_data['pipe2_w'] = pipe2_w
op30_data['pipe2_h'] = pipe2_h
if op30_electricity < 90:
op30_w = op20[2] + pipe2_w - op30_electricity * 0.11
op30_w = round(op30_w, 5)
else:
op30_w = op20[2] + pipe2_w - 10
op30_w = round(op30_w, 5)
op30_l = op20[1]
op30_data['op30_l'] = op20[1]
op30_data['op30_w'] = op30_w
op30_h = op20[3]
op30_data['op30_h'] = op20[3]
op30_data['op30_electricity'] = op30_electricity
op30_data['op30_process_time'] = op30_process_time
if (op30_l < 199.99) or (op30_l > 200.01):
length_test = 1
else:
length_test = 0
if (op30_w < 179.99) or (op30_w > 180.01):
width_test = 1
else:
width_test = 0
if (op30_h < 59.99) or (op30_h > 60.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
op30_test = 'OK'
op30_data['op30_test'] = op30_test
else:
op30_test = 'NOK'
op30_data['op30_test'] = op30_test
# 부품 테스트
if (pipe2_l < 29.99) or (pipe2_l > 30.01):
length_test = 1
else:
length_test = 0
if (pipe2_w < 49.99) or (pipe2_w > 50.01):
width_test = 1
else:
width_test = 0
if (pipe2_h < 29.99) or (pipe2_h > 30.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
pipe2_test = 'OK'
else:
pipe2_test = 'NOK'
now = op20[5]
time_stamp = now + timedelta(seconds=10)
op30_data['op30_time_stamp'] = time_stamp
time_stamp = str(time_stamp)
product_key = time_stamp + product_key
op30_data['product_key'] = product_key
# product_history 적재
product_history_data_list = []
product_history_insert = {}
op30_master_data = product_master.op30_WIP(1)
product_code = op30_master_data['product_code']
product_history_insert['product_key'] = product_key
product_history_insert['product_code'] = product_code
product_history_insert['product_timestamp'] = time_stamp
product_history_data_list.append(product_history_insert)
MySQL_query.insert_product_history(
product_history_data_list) # 히스토리 데이터 DB 적재
# 부품 데이터 모아서 적재 (pipe2)
part_data_list = []
part_history_insert = {}
part_history_insert['product_key'] = time_stamp + '-pipe2'
part_history_insert['product_code'] = 'pipe2'
part_history_insert['product_timestamp'] = time_stamp
part_data_list.append(part_history_insert)
MySQL_query.insert_product_history(part_data_list) # 히스토리 데이터 DB 적재
# product_quality 적재
product_quality_data_list = [] # 딕셔너리 데이터 저장할 리스트
product_quality_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
product_quality_insert['product_key'] = product_key
product_quality_insert['product_size_l'] = str(op30_l)
product_quality_insert['product_size_w'] = str(op30_w)
product_quality_insert['product_size_h'] = str(op30_h)
product_quality_insert['product_test'] = str(op30_test)
product_quality_insert['product_test_timestamp'] = str(time_stamp)
product_quality_data_list.append(product_quality_insert)
MySQL_query.insert_product_quality(
product_quality_data_list) # 품질 데이터 DB 적재
# 부품 quality 적재 (pipe2)
part_quality_data_list = [] # 딕셔너리 데이터 저장할 리스트
part_quality_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
part_quality_insert['product_key'] = time_stamp + '-pipe2'
part_quality_insert['product_size_l'] = str(pipe2_l)
part_quality_insert['product_size_w'] = str(pipe2_w)
part_quality_insert['product_size_h'] = str(pipe2_h)
part_quality_insert['product_test'] = str(pipe2_test)
part_quality_insert['product_test_timestamp'] = str(time_stamp)
part_quality_data_list.append(part_quality_insert)
MySQL_query.insert_product_quality(
part_quality_data_list) # 품질 데이터 DB 적재
# machine 적재
machine_data_list = [] # 딕셔너리 데이터 저장할 리스트
machine_data_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
machine_master_data = machine_master.op30(1) # machine_code 가져오기
machine_code = machine_master_data['machine_code']
machine_data_insert['machine_code'] = machine_code
machine_data_insert['product_key'] = product_key
machine_data_insert['start_time'] = str(now)
machine_data_insert['end_time'] = str(time_stamp)
machine_data_insert['makespan'] = '123'
machine_data_insert['process_time'] = str(op30_process_time)
machine_data_insert['machine_data'] = str(op30_electricity)
machine_data_insert['machine_data_code'] = 'E01'
machine_data_list.append(machine_data_insert)
MySQL_query.insert_machine(machine_data_list) # machine 데이터 DB 적재
return op30_data
def op10(body):
op10_data = {}
std = 0.0025 # 표준편차
product_key = body[0] # 값 리스트 받을 때 첫번째 요소
wavyfin_l = np.random.normal(100, std)
wavyfin_l = round(wavyfin_l, 5)
wavyfin_w = np.random.normal(50, std)
wavyfin_w = round(wavyfin_w, 5)
wavyfin_h = np.random.normal(60, std)
wavyfin_h = round(wavyfin_h, 5)
op10_electricity = np.random.uniform(89.75, 100) # 균일 분포 / (최소, 최대)
op10_electricity = round(op10_electricity, 5)
op10_data['body_l'] = body[1]
op10_data['body_w'] = body[2]
op10_data['body_h'] = body[3]
op10_data['wavyfin_l'] = wavyfin_l
op10_data['wavyfin_w'] = wavyfin_w
op10_data['wavyfin_h'] = wavyfin_h
op10_l = body[1] # 값이 안바껴서 그대로 둠
op10_data['op10_l'] = op10_l
op10_w = body[2]
op10_data['op10_w'] = op10_w
op10_h = wavyfin_h
op10_data['op10_h'] = op10_h
op10_process_time = body[4]
op10_data['op10_electricity'] = op10_electricity
op10_data['op10_process_time'] = op10_process_time
# 재공품 테스트
if (op10_l < 199.99) or (op10_l > 200.01):
length_test = 1
else:
length_test = 0
if (op10_w < 99.99) or (op10_w > 100.01):
width_test = 1
else:
width_test = 0
if (op10_h < 59.99) or (op10_h > 60.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
op10_test = 'OK'
op10_data['op10_test'] = op10_test
else:
op10_test = 'NOK'
op10_data['op10_test'] = op10_test
# 부품 테스트 (body)
if (body[1] < 199.99) or (body[1] > 200.01):
length_test = 1
else:
length_test = 0
if (body[2] < 99.99) or (body[2] > 100.01):
width_test = 1
else:
width_test = 0
if (body[3] < 49.99) or (body[3] > 50.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
body_test = 'OK'
else:
body_test = 'NOK'
# 부품 테스트
if (wavyfin_l < 99.99) or (wavyfin_l > 100.01):
length_test = 1
else:
length_test = 0
if (wavyfin_w < 49.99) or (wavyfin_w > 50.01):
width_test = 1
else:
width_test = 0
if (wavyfin_h < 59.99) or (wavyfin_h > 60.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
wavyfin_test = 'OK'
else:
wavyfin_test = 'NOK'
now = body[5] # 현재 시간
time_stamp = now + timedelta(
seconds=10) # 현재 시간에서 가동시간만큼 추가된 시간 / 형식 = datetime
op10_data['op10_time_stamp'] = time_stamp # 추가된 시간이 완료되고 나가는 시간
time_stamp = str(time_stamp) # 문자형으로 저장
product_key = time_stamp + product_key # 키는 시간 + 아이템 정보로 저장
op10_data['product_key'] = product_key
# product_history 적재
product_history_data_list = []
product_history_insert = {}
op10_master_data = product_master.op10_WIP(1)
product_code = op10_master_data['product_code']
product_history_insert['product_key'] = product_key
product_history_insert['product_code'] = product_code
product_history_insert['product_timestamp'] = time_stamp
product_history_data_list.append(product_history_insert)
MySQL_query.insert_product_history(
product_history_data_list) # 히스토리 데이터 DB 적재
# 부품 히스토리 데이터 모아서 적재 (body)
part_data_list_body = []
part_history_insert_body = {}
part_history_insert_body['product_key'] = time_stamp + '-body'
part_history_insert_body['product_code'] = 'body'
part_history_insert_body['product_timestamp'] = time_stamp
part_data_list_body.append(part_history_insert_body)
MySQL_query.insert_product_history(
part_data_list_body) # 히스토리 데이터 DB 적재
# 부품 히스토리 데이터 모아서 적재 (wavyfin)
part_data_list = []
part_history_insert = {}
part_history_insert['product_key'] = time_stamp + '-wavyfin'
part_history_insert['product_code'] = 'wavyfin'
part_history_insert['product_timestamp'] = time_stamp
part_data_list.append(part_history_insert)
MySQL_query.insert_product_history(part_data_list) # 히스토리 데이터 DB 적재
# product_quality 적재
product_quality_data_list = [] # 딕셔너리 데이터 저장할 리스트
product_quality_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
product_quality_insert['product_key'] = product_key
product_quality_insert['product_size_l'] = str(op10_l)
product_quality_insert['product_size_w'] = str(op10_w)
product_quality_insert['product_size_h'] = str(op10_h)
product_quality_insert['product_test'] = str(op10_test)
product_quality_insert['product_test_timestamp'] = str(time_stamp)
product_quality_data_list.append(product_quality_insert)
MySQL_query.insert_product_quality(
product_quality_data_list) # 품질 데이터 DB 적재
# 부품 quality 적재 (body)
part_quality_data_list_body = [] # 딕셔너리 데이터 저장할 리스트
part_quality_insert_body = {} # DB 저장할 데이터 모아주는 딕셔너리
part_quality_insert_body['product_key'] = time_stamp + '-body'
part_quality_insert_body['product_size_l'] = str(body[1])
part_quality_insert_body['product_size_w'] = str(body[2])
part_quality_insert_body['product_size_h'] = str(body[3])
part_quality_insert_body['product_test'] = str(body_test)
part_quality_insert_body['product_test_timestamp'] = str(time_stamp)
part_quality_data_list_body.append(part_quality_insert_body)
MySQL_query.insert_product_quality(
part_quality_data_list_body) # 품질 데이터 DB 적재
# 부품 quality 적재 (wavyfin)
part_quality_data_list = [] # 딕셔너리 데이터 저장할 리스트
part_quality_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
part_quality_insert['product_key'] = time_stamp + '-wavyfin'
part_quality_insert['product_size_l'] = str(wavyfin_l)
part_quality_insert['product_size_w'] = str(wavyfin_w)
part_quality_insert['product_size_h'] = str(wavyfin_h)
part_quality_insert['product_test'] = str(wavyfin_test)
part_quality_insert['product_test_timestamp'] = str(time_stamp)
part_quality_data_list.append(part_quality_insert)
MySQL_query.insert_product_quality(
part_quality_data_list) # 품질 데이터 DB 적재
# machine 적재
machine_data_list = [] # 딕셔너리 데이터 저장할 리스트
machine_data_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
machine_master_data = machine_master.op10(1) # machine_code 가져오기
machine_code = machine_master_data['machine_code']
machine_data_insert['machine_code'] = machine_code
machine_data_insert['product_key'] = product_key
machine_data_insert['start_time'] = str(now)
machine_data_insert['end_time'] = str(time_stamp)
machine_data_insert['makespan'] = '123'
machine_data_insert['process_time'] = str(op10_process_time)
machine_data_insert['machine_data'] = str(op10_electricity)
machine_data_insert['machine_data_code'] = 'E01'
machine_data_list.append(machine_data_insert)
MySQL_query.insert_machine(machine_data_list) # machine 데이터 DB 적재
return op10_data
from SQL import MySQL_query from machine_master_table import machine_master op10 = machine_master.op10(1) op20 = machine_master.op20(1) op30 = machine_master.op30(1) op40 = machine_master.op40(1) op50 = machine_master.op50(1) op60 = machine_master.op60(1) MySQL_query.insert_machine_master(op10) MySQL_query.insert_machine_master(op20) MySQL_query.insert_machine_master(op30) MySQL_query.insert_machine_master(op40) MySQL_query.insert_machine_master(op50) MySQL_query.insert_machine_master(op60)
def Predict_data():
key_list = MySQL_query.get_product_key_for_test(app.predict_count)
total_big_bottle = []
for i in range(len(key_list)):
total_dict = {}
key30 = key_list[i]['key30']
key20 = key_list[i]['key20']
key10 = key_list[i]['key10']
predict_result = key_list[i]['predict_result']
op30_data = MySQL_query.get_test_data_op30(key30)
op20_data = MySQL_query.get_test_data_op20(key20)
op10_data = MySQL_query.get_test_data_op10(key10)
body_data = MySQL_query.get_test_data_parts_body(key10)
wavyfin_data = MySQL_query.get_test_data_parts_wavyfin(key10)
pipe1_data = MySQL_query.get_test_data_parts_pipe1(key20)
pipe2_data = MySQL_query.get_test_data_parts_pipe2(key30)
product_key = op30_data[0]['product_key']
body_size_l = body_data[0]['product_size_l']
body_size_w = body_data[0]['product_size_w']
body_size_h = body_data[0]['product_size_h']
wavyfin_size_l = wavyfin_data[0]['product_size_l']
wavyfin_size_w = wavyfin_data[0]['product_size_w']
wavyfin_size_h = wavyfin_data[0]['product_size_h']
pipe1_size_l = pipe1_data[0]['product_size_l']
pipe1_size_w = pipe1_data[0]['product_size_w']
pipe1_size_h = pipe1_data[0]['product_size_h']
pipe2_size_l = pipe2_data[0]['product_size_l']
pipe2_size_w = pipe2_data[0]['product_size_w']
pipe2_size_h = pipe2_data[0]['product_size_h']
op10_machine_data = op10_data[0]['machine_data']
op10_size_l = op10_data[0]['product_size_l']
op10_size_w = op10_data[0]['product_size_w']
op10_size_h = op10_data[0]['product_size_h']
op20_machine_data = op20_data[0]['machine_data']
op20_size_l = op20_data[0]['product_size_l']
op20_size_w = op20_data[0]['product_size_w']
op20_size_h = op20_data[0]['product_size_h']
op30_machine_data = op30_data[0]['machine_data']
op30_size_l = op30_data[0]['product_size_l']
op30_size_w = op30_data[0]['product_size_w']
op30_size_h = op30_data[0]['product_size_h']
total_dict['product_key'] = product_key
total_dict['body_size_l'] = str(body_size_l)
total_dict['body_size_w'] = str(body_size_w)
total_dict['body_size_h'] = str(body_size_h)
total_dict['wavyfin_size_l'] = str(wavyfin_size_l)
total_dict['wavyfin_size_w'] = str(wavyfin_size_w)
total_dict['wavyfin_size_h'] = str(wavyfin_size_h)
total_dict['op10_machine_data'] = str(op10_machine_data)
total_dict['op10_size_l'] = str(op10_size_l)
total_dict['op10_size_w'] = str(op10_size_w)
total_dict['op10_size_h'] = str(op10_size_h)
total_dict['pipe1_size_l'] = str(pipe1_size_l)
total_dict['pipe1_size_w'] = str(pipe1_size_w)
total_dict['pipe1_size_h'] = str(pipe1_size_h)
total_dict['op20_machine_data'] = str(op20_machine_data)
total_dict['op20_size_l'] = str(op20_size_l)
total_dict['op20_size_w'] = str(op20_size_w)
total_dict['op20_size_h'] = str(op20_size_h)
total_dict['pipe2_size_l'] = str(pipe2_size_l)
total_dict['pipe2_size_w'] = str(pipe2_size_w)
total_dict['pipe2_size_h'] = str(pipe2_size_h)
total_dict['op30_machine_data'] = str(op30_machine_data)
total_dict['op30_size_l'] = str(op30_size_l)
total_dict['op30_size_w'] = str(op30_size_w)
total_dict['op30_size_h'] = str(op30_size_h)
total_dict['predict_result'] = str(predict_result)
total_big_bottle.append(total_dict)
app.predict_count += 1
if app.predict_count >= 10:
app.predict_count = 10
return jsonify(total_big_bottle)
def Search_data(key60):
key = key60
total_big_bottle = []
data_dict = {}
index1 = 0
bar_count = 0
for index in range(len(key)):
if key[index] == '-':
bar_count = bar_count + 1
if bar_count == 3:
index1 = index
break
key60_head = key[index1 + 1:]
key50_head = key60_head.replace('W6', 'W5')
key40_head = key50_head.replace('W5', 'W4')
key30_head = key40_head.replace('W4', 'W3')
key20_head = key30_head.replace('W3', 'W2')
key10_head = key20_head.replace('W2', 'W1')
key50 = MySQL_query.get_key_for_search(key50_head)
key50 = key50[0]['product_key']
key40 = MySQL_query.get_key_for_search(key40_head)
key40 = key40[0]['product_key']
key30 = MySQL_query.get_key_for_search(key30_head)
key30 = key30[0]['product_key']
key20 = MySQL_query.get_key_for_search(key20_head)
key20 = key20[0]['product_key']
key10 = MySQL_query.get_key_for_search(key10_head)
key10 = key10[0]['product_key']
body_data = MySQL_query.get_body_data_for_search(key10)
wavyfin_data = MySQL_query.get_wavyfin_data_for_search(key10)
pipe1_data = MySQL_query.get_pipe1_data_for_search(key20)
pipe2_data = MySQL_query.get_pipe2_data_for_search(key30)
flange1_data = MySQL_query.get_flange1_data_for_search(key40)
flange2_data = MySQL_query.get_flange2_data_for_search(key50)
op10_data = MySQL_query.get_op10_data_for_search(key10)
op20_data = MySQL_query.get_op20_data_for_search(key20)
op30_data = MySQL_query.get_op30_data_for_search(key30)
op40_data = MySQL_query.get_op40_data_for_search(key40)
op50_data = MySQL_query.get_op50_data_for_search(key50)
op60_data = MySQL_query.get_op60_data_for_search(key60)
product_key = op60_data[0]['product_key']
op60_timestamp = op60_data[0]['product_test_timestamp']
op50_machine_data = op50_data[0]['machine_data']
op50_process_time = op50_data[0]['process_time']
op50_product_size_l = op50_data[0]['product_size_l']
op50_product_size_w = op50_data[0]['product_size_w']
op50_product_size_h = op50_data[0]['product_size_h']
flange2_l = flange2_data[0]['product_size_l']
flange2_w = flange2_data[0]['product_size_w']
flange2_h = flange2_data[0]['product_size_h']
op40_machine_data = op40_data[0]['machine_data']
op40_process_time = op40_data[0]['process_time']
op40_product_size_l = op40_data[0]['product_size_l']
op40_product_size_w = op40_data[0]['product_size_w']
op40_product_size_h = op40_data[0]['product_size_h']
flange1_l = flange1_data[0]['product_size_l']
flange1_w = flange1_data[0]['product_size_w']
flange1_h = flange1_data[0]['product_size_h']
op30_machine_data = op30_data[0]['machine_data']
op30_process_time = op30_data[0]['process_time']
op30_product_size_l = op30_data[0]['product_size_l']
op30_product_size_w = op30_data[0]['product_size_w']
op30_product_size_h = op30_data[0]['product_size_h']
pipe2_l = pipe2_data[0]['product_size_l']
pipe2_w = pipe2_data[0]['product_size_w']
pipe2_h = pipe2_data[0]['product_size_h']
op20_machine_data = op20_data[0]['machine_data']
op20_process_time = op20_data[0]['process_time']
op20_product_size_l = op20_data[0]['product_size_l']
op20_product_size_w = op20_data[0]['product_size_w']
op20_product_size_h = op20_data[0]['product_size_h']
pipe1_l = pipe1_data[0]['product_size_l']
pipe1_w = pipe1_data[0]['product_size_w']
pipe1_h = pipe1_data[0]['product_size_h']
op10_machine_data = op10_data[0]['machine_data']
op10_process_time = op10_data[0]['process_time']
op10_product_size_l = op10_data[0]['product_size_l']
op10_product_size_w = op10_data[0]['product_size_w']
op10_product_size_h = op10_data[0]['product_size_h']
wavyfin_l = wavyfin_data[0]['product_size_l']
wavyfin_w = wavyfin_data[0]['product_size_w']
wavyfin_h = wavyfin_data[0]['product_size_h']
body_l = body_data[0]['product_size_l']
body_w = body_data[0]['product_size_w']
body_h = body_data[0]['product_size_h']
data_dict['product_key'] = product_key
data_dict['op60_timestamp'] = op60_timestamp
data_dict['body_l'] = body_l
data_dict['body_w'] = body_w
data_dict['body_h'] = body_h
data_dict['wavyfin_l'] = wavyfin_l
data_dict['wavyfin_w'] = wavyfin_w
data_dict['wavyfin_h'] = wavyfin_h
data_dict['op10_machine_data'] = op10_machine_data
data_dict['op10_process_time'] = op10_process_time
data_dict['op10_product_size_l'] = op10_product_size_l
data_dict['op10_product_size_w'] = op10_product_size_w
data_dict['op10_product_size_h'] = op10_product_size_h
data_dict['pipe1_l'] = pipe1_l
data_dict['pipe1_w'] = pipe1_w
data_dict['pipe1_h'] = pipe1_h
data_dict['op20_machine_data'] = op20_machine_data
data_dict['op20_process_time'] = op20_process_time
data_dict['op20_product_size_l'] = op20_product_size_l
data_dict['op20_product_size_w'] = op20_product_size_w
data_dict['op20_product_size_h'] = op20_product_size_h
data_dict['pipe2_l'] = pipe2_l
data_dict['pipe2_w'] = pipe2_w
data_dict['pipe2_h'] = pipe2_h
data_dict['op30_machine_data'] = op30_machine_data
data_dict['op30_process_time'] = op30_process_time
data_dict['op30_product_size_l'] = op30_product_size_l
data_dict['op30_product_size_w'] = op30_product_size_w
data_dict['op30_product_size_h'] = op30_product_size_h
data_dict['flange1_l'] = flange1_l
data_dict['flange1_w'] = flange1_w
data_dict['flange1_h'] = flange1_h
data_dict['op40_machine_data'] = op40_machine_data
data_dict['op40_process_time'] = op40_process_time
data_dict['op40_product_size_l'] = op40_product_size_l
data_dict['op40_product_size_w'] = op40_product_size_w
data_dict['op40_product_size_h'] = op40_product_size_h
data_dict['flange2_l'] = flange2_l
data_dict['flange2_w'] = flange2_w
data_dict['flange2_h'] = flange2_h
data_dict['op50_machine_data'] = op50_machine_data
data_dict['op50_process_time'] = op50_process_time
data_dict['op50_product_size_l'] = op50_product_size_l
data_dict['op50_product_size_w'] = op50_product_size_w
data_dict['op50_product_size_h'] = op50_product_size_h
total_big_bottle.append(data_dict)
return total_big_bottle
def machine_master():
machine_master_data = []
### 10
master_dict = {}
machine_code = 'OP10' # 설비 코드명
machine_class = 'MCO1' # 단순 조립
machine_process_time = 'exp10'
machine_assembly = 'body_wavyfin'
machine_data_code = 'E01'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
### 20
master_dict = {}
machine_code = 'OP20' # 설비 코드명
machine_class = 'MCO1' # 단순 조립
machine_process_time = 'exp10'
machine_assembly = 'op10_pipe1'
machine_data_code = 'E01'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
### 30
master_dict = {}
machine_code = 'OP30' # 설비 코드명
machine_class = 'MCO1' # 단순 조립
machine_process_time = 'exp10'
machine_assembly = 'op20_pipe2'
machine_data_code = 'E01'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
### 40
master_dict = {}
machine_code = 'OP40' # 설비 코드명
machine_class = 'MCO2' # 용접 조립
machine_process_time = 'exp10'
machine_assembly = 'op30_flange1'
machine_data_code = 'T01'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
### 50
master_dict = {}
machine_code = 'OP50' # 설비 코드명
machine_class = 'MCO2' # 용접 조립
machine_process_time = 'exp10'
machine_assembly = 'op40_flange2'
machine_data_code = 'T01'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
### 60
master_dict = {}
machine_code = 'OP60' # 설비 코드명
machine_class = 'MCO3' # 최종 검사
machine_process_time = 'exp10'
machine_assembly = 'final_test'
machine_data_code = 'TEST'
master_dict['machine_code'] = machine_code # PK
master_dict['machine_class'] = machine_class
master_dict['machine_process_time'] = machine_process_time
master_dict['machine_assembly'] = machine_assembly
master_dict['machine_data_code'] = machine_data_code
machine_master_data.append(master_dict)
MySQL_query.insert_machine_master(machine_master_data)
return machine_master_data
def op50(op40):
op50_data = {}
std = 0.0025
product_key = op40[0]
flange2_l = np.random.normal(30, std)
flange2_l = round(flange2_l, 5)
flange2_w = np.random.normal(80, std)
flange2_w = round(flange2_w, 5)
flange2_h = np.random.normal(40, std)
flange2_h = round(flange2_h, 5)
op50_process_time = op40[4]
op50_temperature = np.random.uniform(489.75, 510.25)
op50_temperature = round(op50_temperature, 5)
op50_data['flange2_l'] = flange2_l
op50_data['flange2_w'] = flange2_w
op50_data['flange2_h'] = flange2_h
if 490 < op50_temperature < 510:
op50_l = op40[1] + flange2_l
op50_l = round(op50_l, 5)
else:
op50_l = op40[1] + flange2_l - 1
op50_data['op50_l'] = op50_l
op50_w = op40[2]
op50_data['op50_w'] = op50_w
op50_h = op40[3]
op50_data['op50_h'] = op50_h
op50_data['op50_temperature'] = op50_temperature
op50_data['op50_process_time'] = op50_process_time
if (op50_l < 259.99) or (op50_l > 260.01):
length_test = 1
else:
length_test = 0
if (op50_w < 179.99) or (op50_w > 180.01):
width_test = 1
else:
width_test = 0
if (op50_h < 59.99) or (op50_h > 60.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
op50_test = 'OK'
op50_data['op50_test'] = op50_test
else:
op50_test = 'NOK'
op50_data['op50_test'] = op50_test
# 부품 테스트
if (flange2_l < 29.99) or (flange2_l > 30.01):
length_test = 1
else:
length_test = 0
if (flange2_w < 79.99) or (flange2_w > 80.01):
width_test = 1
else:
width_test = 0
if (flange2_h < 39.99) or (flange2_h > 40.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
flange2_test = 'OK'
else:
flange2_test = 'NOK'
now = op40[5]
time_stamp = now + timedelta(seconds=10)
op50_data['op50_time_stamp'] = time_stamp
time_stamp = str(time_stamp)
product_key = time_stamp + product_key
op50_data['product_key'] = product_key
# product_history 적재
product_history_data_list = []
product_history_insert = {}
op50_master_data = product_master.op50_WIP(1)
product_code = op50_master_data['product_code']
product_history_insert['product_key'] = product_key
product_history_insert['product_code'] = product_code
product_history_insert['product_timestamp'] = time_stamp
product_history_data_list.append(product_history_insert)
MySQL_query.insert_product_history(
product_history_data_list) # 히스토리 데이터 DB 적재
# 부품 데이터 모아서 적재 (flange2)
part_data_list = []
part_history_insert = {}
part_history_insert['product_key'] = time_stamp + '-flange2'
part_history_insert['product_code'] = 'flange2'
part_history_insert['product_timestamp'] = time_stamp
part_data_list.append(part_history_insert)
MySQL_query.insert_product_history(part_data_list) # 히스토리 데이터 DB 적재
# product_quality 적재
product_quality_data_list = [] # 딕셔너리 데이터 저장할 리스트
product_quality_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
product_quality_insert['product_key'] = product_key
product_quality_insert['product_size_l'] = str(op50_l)
product_quality_insert['product_size_w'] = str(op50_w)
product_quality_insert['product_size_h'] = str(op50_h)
product_quality_insert['product_test'] = str(op50_test)
product_quality_insert['product_test_timestamp'] = str(time_stamp)
product_quality_data_list.append(product_quality_insert)
MySQL_query.insert_product_quality(
product_quality_data_list) # 품질 데이터 DB 적재
# product_quality 적재
product_quality_data_list = [] # 딕셔너리 데이터 저장할 리스트
product_quality_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
product_quality_insert['product_key'] = time_stamp + '-flange2'
product_quality_insert['product_size_l'] = str(flange2_l)
product_quality_insert['product_size_w'] = str(flange2_w)
product_quality_insert['product_size_h'] = str(flange2_h)
product_quality_insert['product_test'] = str(flange2_test)
product_quality_insert['product_test_timestamp'] = str(time_stamp)
product_quality_data_list.append(product_quality_insert)
MySQL_query.insert_product_quality(
product_quality_data_list) # 품질 데이터 DB 적재
# machine 적재
machine_data_list = [] # 딕셔너리 데이터 저장할 리스트
machine_data_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
machine_master_data = machine_master.op50(1) # machine_code 가져오기
machine_code = machine_master_data['machine_code']
machine_data_insert['machine_code'] = machine_code
machine_data_insert['product_key'] = product_key
machine_data_insert['start_time'] = str(now)
machine_data_insert['end_time'] = str(time_stamp)
machine_data_insert['makespan'] = '123'
machine_data_insert['process_time'] = str(op50_process_time)
machine_data_insert['machine_data'] = str(op50_temperature)
machine_data_insert['machine_data_code'] = 'T01'
machine_data_list.append(machine_data_insert)
MySQL_query.insert_machine(machine_data_list) # machine 데이터 DB 적재
return op50_data
def train():
machine_data = MySQL_query.get_machine_data_list_for_predict(1)
quality_data = MySQL_query.get_quality_data_list_for_predict(1)
machine_df = pd.DataFrame(machine_data)
quality_df = pd.DataFrame(quality_data)
product_key_list = []
body_l_list = []
body_w_list = []
body_h_list = []
wavyfin_l_list = []
wavyfin_w_list = []
wavyfin_h_list = []
op10_l_list = []
op10_w_list = []
op10_h_list = []
pipe1_l_list = []
pipe1_w_list = []
pipe1_h_list = []
op20_l_list = []
op20_w_list = []
op20_h_list = []
pipe2_l_list = []
pipe2_w_list = []
pipe2_h_list = []
op30_l_list = []
op30_w_list = []
op30_h_list = []
flange1_l_list = []
flange1_w_list = []
flange1_h_list = []
op40_l_list = []
op40_w_list = []
op40_h_list = []
flange2_l_list = []
flange2_w_list = []
flange2_h_list = []
op50_l_list = []
op50_w_list = []
op50_h_list = []
op60_l_list = []
op60_w_list = []
op60_h_list = []
op10_electricity_list = []
op10_process_time_list = []
op20_electricity_list = []
op20_process_time_list = []
op30_electricity_list = []
op30_process_time_list = []
op40_temperature_list = []
op40_process_time_list = []
op50_temperature_list = []
op50_process_time_list = []
op60_process_time_list = []
op10_test_list = []
op20_test_list = []
op30_test_list = []
op40_test_list = []
op50_test_list = []
op60_test_list = []
op10_timestamp = []
op20_timestamp = []
op30_timestamp = []
op40_timestamp = []
op50_timestamp = []
op60_timestamp = []
for instance in quality_data:
if (instance['product_key'][27:29] == 'W6'):
product_key_list.append(instance['product_key'])
if (instance['product_key'][27:] == 'body'):
body_l_list.append(instance['product_size_l'])
body_w_list.append(instance['product_size_w'])
body_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:] == 'wavyfin'):
wavyfin_l_list.append(instance['product_size_l'])
wavyfin_w_list.append(instance['product_size_w'])
wavyfin_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W1'):
op10_l_list.append(instance['product_size_l'])
op10_w_list.append(instance['product_size_w'])
op10_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W1'):
if instance['product_test'] == 'OK':
op10_test_list.append(0)
else:
op10_test_list.append(1)
if (instance['product_key'][27:] == 'pipe1'):
pipe1_l_list.append(instance['product_size_l'])
pipe1_w_list.append(instance['product_size_w'])
pipe1_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W2'):
op20_l_list.append(instance['product_size_l'])
op20_w_list.append(instance['product_size_w'])
op20_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W2'):
if instance['product_test'] == 'OK':
op20_test_list.append(0)
else:
op20_test_list.append(1)
if (instance['product_key'][27:] == 'pipe2'):
pipe2_l_list.append(instance['product_size_l'])
pipe2_w_list.append(instance['product_size_w'])
pipe2_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W3'):
op30_l_list.append(instance['product_size_l'])
op30_w_list.append(instance['product_size_w'])
op30_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W3'):
if instance['product_test'] == 'OK':
op30_test_list.append(0)
else:
op30_test_list.append(1)
if (instance['product_key'][27:] == 'flange1'):
flange1_l_list.append(instance['product_size_l'])
flange1_w_list.append(instance['product_size_w'])
flange1_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W4'):
op40_l_list.append(instance['product_size_l'])
op40_w_list.append(instance['product_size_w'])
op40_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W4'):
if instance['product_test'] == 'OK':
op40_test_list.append(0)
else:
op40_test_list.append(1)
if (instance['product_key'][27:] == 'flange2'):
flange2_l_list.append(instance['product_size_l'])
flange2_w_list.append(instance['product_size_w'])
flange2_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W5'):
op50_l_list.append(instance['product_size_l'])
op50_w_list.append(instance['product_size_w'])
op50_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W5'):
if instance['product_test'] == 'OK':
op50_test_list.append(0)
else:
op50_test_list.append(1)
if (instance['product_key'][27:29] == 'W6'):
op60_l_list.append(instance['product_size_l'])
op60_w_list.append(instance['product_size_w'])
op60_h_list.append(instance['product_size_h'])
if (instance['product_key'][27:29] == 'W6'):
if instance['product_test'] == 'OK':
op60_test_list.append(0)
else:
op60_test_list.append(1)
for instance in machine_data:
if (instance['product_key'][27:29] == 'W1'):
op10_electricity_list.append(instance['machine_data'])
if (instance['product_key'][27:29] == 'W1'):
op10_process_time_list.append(instance['process_time'])
if (instance['product_key'][27:29] == 'W1'):
op10_timestamp.append(instance['end_time'])
if (instance['product_key'][27:29] == 'W2'):
op20_electricity_list.append(instance['machine_data'])
if (instance['product_key'][27:29] == 'W2'):
op20_process_time_list.append(instance['process_time'])
if (instance['product_key'][27:29] == 'W2'):
op20_timestamp.append(instance['end_time'])
if (instance['product_key'][27:29] == 'W3'):
op30_electricity_list.append(instance['machine_data'])
if (instance['product_key'][27:29] == 'W3'):
op30_process_time_list.append(instance['process_time'])
if (instance['product_key'][27:29] == 'W3'):
op30_timestamp.append(instance['end_time'])
if (instance['product_key'][27:29] == 'W4'):
op40_temperature_list.append(instance['machine_data'])
if (instance['product_key'][27:29] == 'W4'):
op40_process_time_list.append(instance['process_time'])
if (instance['product_key'][27:29] == 'W4'):
op40_timestamp.append(instance['end_time'])
if (instance['product_key'][27:29] == 'W5'):
op50_temperature_list.append(instance['machine_data'])
if (instance['product_key'][27:29] == 'W5'):
op50_process_time_list.append(instance['process_time'])
if (instance['product_key'][27:29] == 'W5'):
op50_timestamp.append(instance['end_time'])
if (instance['product_key'][27:29] == 'W6'):
op60_process_time_list.append(instance['process_time'])
if (instance['product_key'][27:29] == 'W6'):
op60_timestamp.append(instance['end_time'])
df = pd.DataFrame({
"product_key": product_key_list,
'body_l': body_l_list,
'body_w': body_w_list,
'body_h': body_h_list,
'wavyfin_l': wavyfin_l_list,
'wavyfin_w': wavyfin_w_list,
'wavyfin_h': wavyfin_h_list,
'op10_l': op10_l_list,
'op10_w': op10_w_list,
'op10_h': op10_h_list,
'op10_electricity': op10_electricity_list,
'op10_process_time': op10_process_time_list,
'op10_test': op10_test_list,
'op10_timestamp': op10_timestamp,
'pipe1_l': pipe1_l_list,
'pipe1_w': pipe1_w_list,
'pipe1_h': pipe1_h_list,
'op20_l': op20_l_list,
'op20_w': op20_w_list,
'op20_h': op20_h_list,
'op20_electricity': op20_electricity_list,
'op20_process_time': op20_process_time_list,
'op20_test': op20_test_list,
'op20_timestamp': op20_timestamp,
'pipe2_l': pipe2_l_list,
'pipe2_w': pipe2_w_list,
'pipe2_h': pipe2_h_list,
'op30_l': op30_l_list,
'op30_w': op30_w_list,
'op30_h': op30_h_list,
'op30_electricity': op30_electricity_list,
'op30_process_time': op30_process_time_list,
'op30_test': op30_test_list,
'op30_timestamp': op30_timestamp,
'flange1_l': flange1_l_list,
'flange1_w': flange1_w_list,
'flange1_h': flange1_h_list,
'op40_l': op40_l_list,
'op40_w': op40_w_list,
'op40_h': op40_h_list,
'op40_temperature': op40_temperature_list,
'op40_process_time': op40_process_time_list,
'op40_test': op40_test_list,
'op40_timestamp': op40_timestamp,
'flange2_l': flange2_l_list,
'flange2_w': flange2_w_list,
'flange2_h': flange2_h_list,
'op50_l': op50_l_list,
'op50_w': op50_w_list,
'op50_h': op50_h_list,
'op50_temperature': op50_temperature_list,
'op50_process_time': op50_process_time_list,
'op50_test': op50_test_list,
'op50_timestamp': op50_timestamp,
'op60_l': op60_l_list,
'op60_w': op60_w_list,
'op60_h': op60_h_list,
'op60_process_time': op60_process_time_list,
'op60_test': op60_test_list,
'op60_timestamp': op60_timestamp
})
X = df.drop([
'op60_timestamp', 'op60_process_time', 'op60_h', 'op60_w', 'op60_l',
'op60_test', 'op50_timestamp', 'op50_process_time', 'op50_h', 'op50_w',
'op50_l', 'op50_temperature', 'op50_test', 'op40_timestamp',
'op40_process_time', 'op40_h', 'op40_w', 'op40_l', 'op40_temperature',
'op40_test', 'flange1_l', 'flange1_w', 'flange1_h', 'flange2_l',
'flange2_w', 'flange2_h', 'op10_timestamp', 'op20_timestamp',
'op30_timestamp', 'product_key'
],
axis=1)
y = df['op60_test']
X_train, X_test, y_train, y_test = train_test_split(X,
y,
test_size=0.1,
shuffle=False,
random_state=1004)
rf_clf = RandomForestClassifier(random_state=0) # 랜덤 포레스트 모델
rf_clf.fit(X_train, y_train) # 학습
saved_model = pickle.dumps(rf_clf) # 모델 저장
preds = rf_clf.predict(X_test)
accuracy = accuracy_score(y_test, preds)
print('랜덤 포레스트 정확도: {0:.4f}'.format(accuracy))
joblib.dump(rf_clf, 'pretrained_model.pkl')
print("파일 저장완료")
def process_start(amount):
std = 0.0025 # 표준편차 100만개 중에 12개 불량
num = MySQL_query.key_for_count(1) # 키 번호를 매기기 위한 값을 DB에서 가져옴 op10 키
if num == []: # 아무것도 없으면 -> 생산이 안됐음
n = 10001 # 처음 10001 번 품목으로 키값을 찍어라. n은 P10001 <- 요 숫자
else: # 하나라도 있으면
n = num[0][
'product_key'] # ['product_key' : 'xxxx'] n은 키 값 -> str 형식
bar_count = 0 # 키 파싱하기 위한
for index in range(len(n)):
if n[index] == '-':
bar_count = bar_count + 1
if bar_count == 3:
break
n = int(n[index + 4:]) + 1 # 지금까지 만들어진 품목 번호 + 1을 시작값으로 만들겠다.
total_test_data = [] # 예측할 test 데이터들을 뽑기 위한 모음
stop_button = None # 정지 버튼 True 되면 공정 스탑 하고 정지하거나 리셋
##### 전체적인 진행: body 생성 -> op10 실행 -> DB 저장 -> 저장한 데이터 가져오기 -> op10_data 변수 저장 -> 다음 공정 실행
body_P0 = [] # 공정에 넣을 body 데이터 리스트 틀 -> Machine에 넣을 예정
product_key_W1P0 = '-' + 'W1' + 'P' + str(
n) # 첫번째 제품 primary_key 생성 -> machine에서 시간 추가할 예정
body_P0.append(product_key_W1P0)
body_l_P0 = np.random.normal(200, std) # body 치수 데이터 생성
body_l_P0 = round(body_l_P0, 5) # 소수점 5째 자리까지 만들어줘
body_P0.append(body_l_P0) # 리스트에 담기
body_w_P0 = np.random.normal(100, std)
body_w_P0 = round(body_w_P0, 5)
body_P0.append(body_w_P0)
body_h_P0 = np.random.normal(50, std)
body_h_P0 = round(body_h_P0, 5)
body_P0.append(body_h_P0)
op10_process_time_P0 = np.random.triangular(
9, 10, 10) # process_time 생성 (최소, 최대, 최빈)
op10_process_time_P0 = round(op10_process_time_P0, 5)
body_P0.append(op10_process_time_P0)
body_P0.append(
datetime.now() +
timedelta(hours=9)) # 첫번째 제품은 현재시간부터 시작한다고 가정, 한국시간에 맞추기 위해 9시간 추가
print('한개 생산 중')
time.sleep(10) # 10초 텀 실제 시간으로 텀을 주도록 만듬
# op10 공정 실행 (W1P0)
op10_data_P0 = machine_operate.op10(body_P0)
product_key_W1P0 = op10_data_P0['product_key']
##### 여기에 웹페이지로 쏴주는 기능 추가 #####
#################################### W1P0 생산 및 DB 저장 완료 #####################################
# 다음 공정에 넣기 위한 데이터 가져와서 넣기
op10_data_P0_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W1P0)
op10_data_list_P0 = [] # P0 재공품 다음공정으로 넣어줄 데이터 저장할 리스트
op10_l_P0 = op10_data_P0_from_DB[0][
'product_size_l'] # 재공품 치수 데이터 가져오기
op10_w_P0 = op10_data_P0_from_DB[0]['product_size_w']
op10_h_P0 = op10_data_P0_from_DB[0]['product_size_h']
op20_process_time_P0 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time 새로 생성
op20_process_time_P0 = round(op20_process_time_P0, 5)
op20_product_key_P0 = '-' + 'W2' + 'P' + str(n) # 제품 키 생성
op20_start_time_P0 = datetime.now() + timedelta(hours=9)
op10_data_list_P0.append(op20_product_key_P0) # 2번째 제품 키 - 인덱스 0번
op10_data_list_P0.append(op10_l_P0) # 1번 - 길이
op10_data_list_P0.append(op10_w_P0) # 2번 - 너비
op10_data_list_P0.append(op10_h_P0) # 3번 - 높이
op10_data_list_P0.append(
op20_process_time_P0) # 4번 - 다음 공정 작업할 process_time
op10_data_list_P0.append(
op20_start_time_P0
) # 재공품 정보에 시작해야할 시간 저장 / 인덱스 5번 // # op20 넣기위한 리스트를 만들어주고 있음.
body_P1 = [] # P1 제품에 대한 body 값 저장할 리스트
product_key_W1P1 = '-' + 'W1' + 'P' + str(
n + 1) # 첫번째 제품 primary_key 생성 -> machine에서 시간 추가할 예정
body_P1.append(product_key_W1P1)
body_l_P1 = np.random.normal(200, std) # body 치수 데이터 생성
body_l_P1 = round(body_l_P1, 5)
body_P1.append(body_l_P1)
body_w_P1 = np.random.normal(100, std)
body_w_P1 = round(body_w_P1, 5)
body_P1.append(body_w_P1)
body_h_P1 = np.random.normal(50, std)
body_h_P1 = round(body_h_P1, 5)
body_P1.append(body_h_P1)
op10_process_time_P1 = np.random.triangular(9, 10,
10) # process_time 생성
op10_process_time_P1 = round(op10_process_time_P1, 5)
body_P1.append(op10_process_time_P1)
body_P1.append(datetime.now() + timedelta(hours=9))
print('두개 생산 중')
time.sleep(10) # 10초 텀
# op20 공정 실행 (W2P0)
op20_data_P0 = machine_operate.op20(
op10_data_list_P0) # <- 앞공정 재공품 받아서 실행 // 리스트를 넣어줌
product_key_W2P0 = op20_data_P0['product_key']
#################################### W2P0 생산 및 DB 저장 완료 #####################################
# op10 공정 실행 (W1P1)
op10_data_P1 = machine_operate.op10(body_P1)
product_key_W1P1 = op10_data_P1['product_key']
#################################### W1P1 생산 및 DB 저장 완료 #####################################
# 다음 공정에 넣기 위한 데이터 가져오기
op20_data_P0_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W2P0)
# 다음 공정에 넣기 위한 데이터 가져오기
op10_data_P1_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W1P1)
# op20 P0 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op20_data_list_P0 = []
product_key_W3P0 = '-' + 'W3' + 'P' + str(n) # 제품 키 생성
op20_l_P0 = op20_data_P0_from_DB[0]['product_size_l']
op20_w_P0 = op20_data_P0_from_DB[0]['product_size_w']
op20_h_P0 = op20_data_P0_from_DB[0]['product_size_h']
op20_timestamp_P0 = op20_data_P0_from_DB[0][
'product_test_timestamp'] # op20 끝난시간
op30_process_time_P0 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op30_process_time_P0 = round(op30_process_time_P0, 5)
op30_start_time_P0 = datetime.now() + timedelta(hours=9)
op20_data_list_P0.append(product_key_W3P0)
op20_data_list_P0.append(op20_l_P0)
op20_data_list_P0.append(op20_w_P0)
op20_data_list_P0.append(op20_h_P0)
op20_data_list_P0.append(op30_process_time_P0)
op20_data_list_P0.append(op30_start_time_P0)
# op10 P1 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op10_data_list_P1 = []
product_key_W2P1 = '-' + 'W2' + 'P' + str(n + 1) # 제품 키 생성
op10_l_P1 = op10_data_P1_from_DB[0]['product_size_l']
op10_w_P1 = op10_data_P1_from_DB[0]['product_size_w']
op10_h_P1 = op10_data_P1_from_DB[0]['product_size_h']
op10_timestamp_P1 = op10_data_P1_from_DB[0][
'product_test_timestamp'] # op20 끝난시간
op20_process_time_P1 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op20_process_time_P1 = round(op20_process_time_P1, 5)
op20_start_time_P1 = datetime.now() + timedelta(hours=9)
op10_data_list_P1.append(
product_key_W2P1) # 재공품 데이터 -> 다음 공정에 투입 (P1제품)
op10_data_list_P1.append(op10_l_P1)
op10_data_list_P1.append(op10_w_P1)
op10_data_list_P1.append(op10_h_P1)
op10_data_list_P1.append(op20_process_time_P1)
op10_data_list_P1.append(op20_start_time_P1)
body_P2 = [] # P1 제품에 대한 body 값 저장할 리스트
product_key_W1P2 = '-' + 'W1' + 'P' + str(
n + 2) # 첫번째 제품 primary_key 생성 -> machine에서 시간 추가할 예정
body_P2.append(product_key_W1P2)
body_l_P2 = np.random.normal(200, std) # body 치수 데이터 생성
body_l_P2 = round(body_l_P2, 5)
body_P2.append(body_l_P2)
body_w_P2 = np.random.normal(100, std)
body_w_P2 = round(body_w_P2, 5)
body_P2.append(body_w_P2)
body_h_P2 = np.random.normal(50, std)
body_h_P2 = round(body_h_P2, 5)
body_P2.append(body_h_P2)
op10_process_time_P2 = np.random.triangular(9, 10,
10) # process_time 생성
op10_process_time_P2 = round(op10_process_time_P2, 5)
body_P2.append(op10_process_time_P2)
body_P2.append(datetime.now() +
timedelta(hours=9)) # 세번째 제품은 P1 끝난시간부터 시작
# op30, 20, 10 시작
print('세개 생산 중')
time.sleep(10)
# op30 공정 실행 (W3P0)
op30_data_P0 = machine_operate.op30(
op20_data_list_P0) # <- 앞공정 재공품 받아서 실행
pred_P0 = Predict.predict_quality(op10_data_P0, op20_data_P0,
op30_data_P0)
print("P0 예측값 : " + str(pred_P0))
MySQL_query.insert_product_prediction(op30_data_P0, op20_data_P0,
op10_data_P0, pred_P0)
product_key_W3P0 = op30_data_P0['product_key']
#################################### W3P0 생산 및 DB 저장 완료 #####################################
# op20 공정 실행 (W2P1)
op20_data_P1 = machine_operate.op20(
op10_data_list_P1) # <- 앞공정 재공품 받아서 실행
product_key_W2P1 = op20_data_P1['product_key']
#################################### W2P1 생산 및 DB 저장 완료 #####################################
# op10 공정 실행 (W1P2)
op10_data_P2 = machine_operate.op10(body_P2)
product_key_W1P2 = op10_data_P2['product_key']
#################################### W1P2 생산 및 DB 저장 완료 #####################################
# 다음 공정에 넣기 위한 데이터 가져오기
op30_data_P0_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W3P0)
# 다음 공정에 넣기 위한 데이터 가져오기
op20_data_P1_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W2P1)
# 다음 공정에 넣기 위한 데이터 가져오기
op10_data_P2_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W1P2)
# op30 P0 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op30_data_list_P0 = []
product_key_W4P0 = '-' + 'W4' + 'P' + str(n) # 제품 키 생성
op30_l_P0 = op30_data_P0_from_DB[0]['product_size_l']
op30_w_P0 = op30_data_P0_from_DB[0]['product_size_w']
op30_h_P0 = op30_data_P0_from_DB[0]['product_size_h']
op30_timestamp_P0 = op30_data_P0_from_DB[0][
'product_test_timestamp'] # op20 끝난시간
op40_process_time_P0 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op40_process_time_P0 = round(op40_process_time_P0, 5)
op40_start_time_P0 = datetime.now() + timedelta(hours=9)
op30_data_list_P0.append(product_key_W4P0)
op30_data_list_P0.append(op30_l_P0)
op30_data_list_P0.append(op30_w_P0)
op30_data_list_P0.append(op30_h_P0)
op30_data_list_P0.append(op40_process_time_P0)
op30_data_list_P0.append(op40_start_time_P0)
# op20 P1 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op20_data_list_P1 = []
product_key_W3P1 = '-' + 'W3' + 'P' + str(n + 1) # 제품 키 생성
op20_l_P1 = op20_data_P1_from_DB[0]['product_size_l']
op20_w_P1 = op20_data_P1_from_DB[0]['product_size_w']
op20_h_P1 = op20_data_P1_from_DB[0]['product_size_h']
op30_process_time_P1 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op30_process_time_P1 = round(op30_process_time_P1, 5)
op30_start_time_P1 = datetime.now() + timedelta(hours=9)
op20_data_list_P1.append(product_key_W3P1)
op20_data_list_P1.append(op20_l_P1)
op20_data_list_P1.append(op20_w_P1)
op20_data_list_P1.append(op20_h_P1)
op20_data_list_P1.append(op30_process_time_P1)
op20_data_list_P1.append(op30_start_time_P1)
# op10 P2 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op10_data_list_P2 = []
product_key_W2P2 = '-' + 'W2' + 'P' + str(n + 2) # 제품 키 생성
op10_l_P2 = op10_data_P2_from_DB[0]['product_size_l']
op10_w_P2 = op10_data_P2_from_DB[0]['product_size_w']
op10_h_P2 = op10_data_P2_from_DB[0]['product_size_h']
op20_process_time_P2 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op20_process_time_P2 = round(op20_process_time_P2, 5)
op20_start_time_P2 = datetime.now() + timedelta(hours=9)
op10_data_list_P2.append(product_key_W2P2)
op10_data_list_P2.append(op10_l_P2)
op10_data_list_P2.append(op10_w_P2)
op10_data_list_P2.append(op10_h_P2)
op10_data_list_P2.append(op20_process_time_P2)
op10_data_list_P2.append(op20_start_time_P2)
body_P3 = [] # P3 제품에 대한 body 값 저장할 리스트
product_key_W1P3 = '-' + 'W1' + 'P' + str(
n + 3) # 첫번째 제품 primary_key 생성 -> machine에서 시간 추가할 예정
body_P3.append(product_key_W1P3)
body_l_P2 = np.random.normal(200, std) # body 치수 데이터 생성
body_l_P2 = round(body_l_P2, 5)
body_P3.append(body_l_P2)
body_w_P2 = np.random.normal(100, std)
body_w_P2 = round(body_w_P2, 5)
body_P3.append(body_w_P2)
body_h_P2 = np.random.normal(50, std)
body_h_P2 = round(body_h_P2, 5)
body_P3.append(body_h_P2)
op10_process_time_P2 = np.random.triangular(9, 10,
10) # process_time 생성
op10_process_time_P2 = round(op10_process_time_P2, 5)
body_P3.append(op10_process_time_P2)
body_P3.append(datetime.now() + timedelta(hours=9))
print('네개 생산 중')
time.sleep(10)
# op40 공정 실행 (W4P0)
op40_data_P0 = machine_operate.op40(
op30_data_list_P0) # <- 앞공정 재공품 받아서 실행
product_key_W4P0 = op40_data_P0['product_key']
#################################### W4P0 생산 및 DB 저장 완료 #####################################
# op30 공정 실행 (W3P1)
op30_data_P1 = machine_operate.op30(
op20_data_list_P1) # <- 앞공정 재공품 받아서 실행
pred_P1 = Predict.predict_quality(op10_data_P1, op20_data_P1,
op30_data_P1)
print("P1 예측값 : " + str(pred_P1))
MySQL_query.insert_product_prediction(op30_data_P1, op20_data_P1,
op10_data_P1, pred_P1)
product_key_W3P1 = op30_data_P1['product_key']
#################################### W3P1 생산 및 DB 저장 완료 #####################################
# op20 공정 실행 (W2P2)
op20_data_P2 = machine_operate.op20(op10_data_list_P2)
product_key_W2P2 = op20_data_P2['product_key']
#################################### W2P2 생산 및 DB 저장 완료 #####################################
# op10 공정 실행 (W1P3)
op10_data_P3 = machine_operate.op10(body_P3)
product_key_W1P3 = op10_data_P3['product_key']
total_test_data.append(op10_data_P3)
#################################### W1P3 생산 및 DB 저장 완료 #####################################
# 다음 공정에 넣기 위한 데이터 가져오기
op40_data_P0_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W4P0)
# 다음 공정에 넣기 위한 데이터 가져오기
op30_data_P1_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W3P1)
# 다음 공정에 넣기 위한 데이터 가져오기
op20_data_P2_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W2P2)
# 다음 공정에 넣기 위한 데이터 가져오기
op10_data_P3_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W1P3)
# op40 P0 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op40_data_list_P0 = []
product_key_W5P0 = '-' + 'W5' + 'P' + str(n) # 제품 키 생성
op40_l_P0 = op40_data_P0_from_DB[0]['product_size_l']
op40_w_P0 = op40_data_P0_from_DB[0]['product_size_w']
op40_h_P0 = op40_data_P0_from_DB[0]['product_size_h']
op40_timestamp_P0 = op40_data_P0_from_DB[0][
'product_test_timestamp'] # op20 끝난시간
op50_process_time_P0 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op50_process_time_P0 = round(op50_process_time_P0, 5)
op50_start_time_P0 = datetime.now() + timedelta(hours=9)
op40_data_list_P0.append(product_key_W5P0)
op40_data_list_P0.append(op40_l_P0)
op40_data_list_P0.append(op40_w_P0)
op40_data_list_P0.append(op40_h_P0)
op40_data_list_P0.append(op50_process_time_P0)
op40_data_list_P0.append(op50_start_time_P0)
# op30 P1 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op30_data_list_P1 = []
product_key_W4P1 = '-' + 'W4' + 'P' + str(n + 1) # 제품 키 생성
op30_l_P1 = op30_data_P1_from_DB[0]['product_size_l']
op30_w_P1 = op30_data_P1_from_DB[0]['product_size_w']
op30_h_P1 = op30_data_P1_from_DB[0]['product_size_h']
op30_timestamp_P1 = op30_data_P1_from_DB[0][
'product_test_timestamp'] # op30 끝난시간
op40_process_time_P1 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op40_process_time_P1 = round(op40_process_time_P1, 5)
op40_start_time_P1 = datetime.now() + timedelta(hours=9)
op30_data_list_P1.append(product_key_W4P1)
op30_data_list_P1.append(op30_l_P1)
op30_data_list_P1.append(op30_w_P1)
op30_data_list_P1.append(op30_h_P1)
op30_data_list_P1.append(op40_process_time_P1)
op30_data_list_P1.append(op40_start_time_P1)
# op20 P2 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op20_data_list_P2 = []
product_key_W3P2 = '-' + 'W3' + 'P' + str(n + 2) # 제품 키 생성
op20_l_P2 = op20_data_P2_from_DB[0]['product_size_l']
op20_w_P2 = op20_data_P2_from_DB[0]['product_size_w']
op20_h_P2 = op20_data_P2_from_DB[0]['product_size_h']
op30_process_time_P2 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op30_process_time_P2 = round(op30_process_time_P2, 5)
op30_start_time_P2 = datetime.now() + timedelta(hours=9)
op20_data_list_P2.append(product_key_W3P2)
op20_data_list_P2.append(op20_l_P2)
op20_data_list_P2.append(op20_w_P2)
op20_data_list_P2.append(op20_h_P2)
op20_data_list_P2.append(op30_process_time_P2)
op20_data_list_P2.append(op30_start_time_P2)
# op10 P1 생산 끝낸 데이터를 다음 공정에 넣을 변수에 저장하기
op10_data_list_P3 = []
product_key_W2P3 = '-' + 'W2' + 'P' + str(n + 3) # 제품 키 생성
op10_l_P3 = op10_data_P3_from_DB[0]['product_size_l']
op10_w_P3 = op10_data_P3_from_DB[0]['product_size_w']
op10_h_P3 = op10_data_P3_from_DB[0]['product_size_h']
op20_process_time_P3 = np.random.triangular(
9, 10, 10) # 다음 공정에 넣어줄 process_time
op20_process_time_P3 = round(op20_process_time_P3, 5)
op20_start_time_P3 = datetime.now() + timedelta(hours=9)
op10_data_list_P3.append(product_key_W2P3)
op10_data_list_P3.append(op10_l_P3)
op10_data_list_P3.append(op10_w_P3)
op10_data_list_P3.append(op10_h_P3)
op10_data_list_P3.append(op20_process_time_P3)
op10_data_list_P3.append(op20_start_time_P3)
body_P4 = [] # P1 제품에 대한 body 값 저장할 리스트
product_key_W1P4 = '-' + 'W1' + 'P' + str(
n + 4) # 첫번째 제품 primary_key 생성 -> machine에서 시간 추가할 예정
body_P4.append(product_key_W1P4)
body_l_P3 = np.random.normal(200, std) # body 치수 데이터 생성
body_l_P3 = round(body_l_P3, 5)
body_P4.append(body_l_P3)
body_w_P3 = np.random.normal(100, std)
body_w_P3 = round(body_w_P3, 5)
body_P4.append(body_w_P3)
body_h_P3 = np.random.normal(50, std)
body_h_P3 = round(body_h_P3, 5)
body_P4.append(body_h_P3)
op10_process_time_P3 = np.random.triangular(9, 10,
10) # process_time 생성
op10_process_time_P3 = round(op10_process_time_P3, 5)
body_P4.append(op10_process_time_P3)
body_P4.append(datetime.now() +
timedelta(hours=9)) # 다섯 번째 제품은 P3 끝난시간부터 시작
print('다섯개 생산 중')
time.sleep(10)
# op50 공정 실행 (W5P0)
op50_data_P0 = machine_operate.op50(
op40_data_list_P0) # <- 앞공정 재공품 받아서 실행
product_key_W5P0 = op50_data_P0['product_key']
#################################### W5P0 생산 및 DB 저장 완료 #####################################
# op40 공정 실행 (W4P1)
op40_data_P1 = machine_operate.op40(
op30_data_list_P1) # <- 앞공정 재공품 받아서 실행
product_key_W4P1 = op40_data_P1['product_key']
#################################### W4P1 생산 및 DB 저장 완료 #####################################
# op30 공정 실행 (W3P2)
op30_data_P2 = machine_operate.op30(
op20_data_list_P2) # <- 앞공정 재공품 받아서 실행
pred_P2 = Predict.predict_quality(op10_data_P2, op20_data_P2,
op30_data_P2)
print("P2 예측값 : " + str(pred_P2))
MySQL_query.insert_product_prediction(op30_data_P2, op20_data_P2,
op10_data_P2, pred_P2)
product_key_W3P2 = op30_data_P2['product_key']
#################################### W3P2 생산 및 DB 저장 완료 #####################################
# op20 공정 실행 (W2P3)
op20_data_P3 = machine_operate.op20(op10_data_list_P3)
product_key_W2P3 = op20_data_P3['product_key']
total_test_data.append(op20_data_P3)
#################################### W2P3 생산 및 DB 저장 완료 #####################################
# op10 공정 실행 (W1P4)
op10_data_P4 = machine_operate.op10(body_P4)
product_key_W1P4 = op10_data_P4['product_key']
total_test_data.append(op10_data_P4)
#################################### W1P4 생산 및 DB 저장 완료 #####################################
# 여기서부터 6개씩 반복
print('for문 진입')
for i in range(n + 5, 100000): # 6번째 제품부터 반복 시작
op10_process_time = np.random.triangular(9, 10, 10)
op10_process_time = round(op10_process_time, 5)
op20_process_time = np.random.triangular(9, 10, 10)
op20_process_time = round(op20_process_time, 5)
op30_process_time = np.random.triangular(9, 10, 10)
op30_process_time = round(op30_process_time, 5)
op40_process_time = np.random.triangular(9, 10, 10)
op40_process_time = round(op40_process_time, 5)
op50_process_time = np.random.triangular(9, 10, 10)
op50_process_time = round(op50_process_time, 5)
op60_process_time = np.random.triangular(9, 10, 10)
op60_process_time = round(op60_process_time, 5)
if i == n + 5: # 딱 처음 for 문 진입했을 때만 실행
op50_data_P0_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W5P0) # 전 공정에서 끝나고 결과 데이터
op50_WIP = [] # op60에 넣기 위한 리스트
product_key_W6P0 = '-' + 'W6' + 'P' + str(i - 5) # key값 부여
op50_l_P0 = op50_data_P0_from_DB[0][
'product_size_l'] # 데이터 나눠서 변수에 저장
op50_w_P0 = op50_data_P0_from_DB[0]['product_size_w']
op50_h_P0 = op50_data_P0_from_DB[0]['product_size_h']
op60_start_time = op50_data_P0_from_DB[0][
'product_test_timestamp']
op50_WIP.append(product_key_W6P0) # 변수에 저장한거 하나씩 리스테에 저장
op50_WIP.append(op50_l_P0)
op50_WIP.append(op50_w_P0)
op50_WIP.append(op50_h_P0)
op50_WIP.append(op60_process_time)
op50_WIP.append(op60_start_time)
op40_data_P1_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W4P1)
op40_WIP = []
product_key_W5P1 = '-' + 'W5' + 'P' + str(i - 4)
op40_l_P1 = op40_data_P1_from_DB[0]['product_size_l']
op40_w_P1 = op40_data_P1_from_DB[0]['product_size_w']
op40_h_P1 = op40_data_P1_from_DB[0]['product_size_h']
op50_start_time = op40_data_P1_from_DB[0][
'product_test_timestamp']
op40_WIP.append(product_key_W5P1)
op40_WIP.append(op40_l_P1)
op40_WIP.append(op40_w_P1)
op40_WIP.append(op40_h_P1)
op40_WIP.append(op50_process_time)
op40_WIP.append(op50_start_time)
op30_data_P2_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W3P2)
op30_WIP = []
product_key_W4P2 = '-' + 'W4' + 'P' + str(i - 3)
op30_l_P2 = op30_data_P2_from_DB[0]['product_size_l']
op30_w_P2 = op30_data_P2_from_DB[0]['product_size_w']
op30_h_P2 = op30_data_P2_from_DB[0]['product_size_h']
op40_start_time = op30_data_P2_from_DB[0][
'product_test_timestamp']
op30_WIP.append(product_key_W4P2)
op30_WIP.append(op30_l_P2)
op30_WIP.append(op30_w_P2)
op30_WIP.append(op30_h_P2)
op30_WIP.append(op40_process_time)
op30_WIP.append(op40_start_time)
op20_data_P3_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W2P3)
op20_WIP = []
product_key_W3P3 = '-' + 'W3' + 'P' + str(i - 2)
op20_l_P3 = op20_data_P3_from_DB[0]['product_size_l']
op20_w_P3 = op20_data_P3_from_DB[0]['product_size_w']
op20_h_P3 = op20_data_P3_from_DB[0]['product_size_h']
op30_start_time = op20_data_P3_from_DB[0][
'product_test_timestamp']
op20_WIP.append(product_key_W3P3)
op20_WIP.append(op20_l_P3)
op20_WIP.append(op20_w_P3)
op20_WIP.append(op20_h_P3)
op20_WIP.append(op30_process_time)
op20_WIP.append(op30_start_time)
op10_data_P4_from_DB = MySQL_query.get_quality_data_for_process(
product_key_W1P4)
op10_WIP = []
product_key_W2P4 = '-' + 'W2' + 'P' + str(i - 1)
op10_l_P4 = op10_data_P4_from_DB[0]['product_size_l']
op10_w_P4 = op10_data_P4_from_DB[0]['product_size_w']
op10_h_P4 = op10_data_P4_from_DB[0]['product_size_h']
op20_start_time = op10_data_P4_from_DB[0][
'product_test_timestamp']
op10_WIP.append(product_key_W2P4)
op10_WIP.append(op10_l_P4)
op10_WIP.append(op10_w_P4)
op10_WIP.append(op10_h_P4)
op10_WIP.append(op20_process_time)
op10_WIP.append(op20_start_time)
op10_time_stamp = datetime.now() + timedelta(hours=9)
else: # 한바퀴 돌고 난 다음
op50_WIP = []
product_key_W6 = '-' + 'W6' + 'P' + str(i - 5)
op50_l = op50_data['op50_l']
op50_w = op50_data['op50_w']
op50_h = op50_data['op50_h']
op50_WIP.append(product_key_W6)
op50_WIP.append(op50_l)
op50_WIP.append(op50_w)
op50_WIP.append(op50_h)
op50_WIP.append(op60_process_time)
op50_WIP.append(datetime.now() + timedelta(hours=9))
op40_WIP = []
product_key_W5 = '-' + 'W5' + 'P' + str(i - 4)
op40_l = op40_data['op40_l']
op40_w = op40_data['op40_w']
op40_h = op40_data['op40_h']
op40_WIP.append(product_key_W5)
op40_WIP.append(op40_l)
op40_WIP.append(op40_w)
op40_WIP.append(op40_h)
op40_WIP.append(op50_process_time)
op40_WIP.append(datetime.now() + timedelta(hours=9))
op30_WIP = []
product_key_W4 = '-' + 'W4' + 'P' + str(i - 3)
op30_l = op30_data['op30_l']
op30_w = op30_data['op30_w']
op30_h = op30_data['op30_h']
op30_WIP.append(product_key_W4)
op30_WIP.append(op30_l)
op30_WIP.append(op30_w)
op30_WIP.append(op30_h)
op30_WIP.append(op40_process_time)
op30_WIP.append(datetime.now() + timedelta(hours=9))
op20_WIP = []
product_key_W3 = '-' + 'W3' + 'P' + str(i - 2)
op20_l = op20_data['op20_l']
op20_w = op20_data['op20_w']
op20_h = op20_data['op20_h']
op20_WIP.append(product_key_W3)
op20_WIP.append(op20_l)
op20_WIP.append(op20_w)
op20_WIP.append(op20_h)
op20_WIP.append(op30_process_time)
op20_WIP.append(datetime.now() + timedelta(hours=9))
op10_WIP = []
product_key_W2 = '-' + 'W2' + 'P' + str(i - 1)
op10_l = op10_data['op10_l']
op10_w = op10_data['op10_w']
op10_h = op10_data['op10_h']
op10_WIP.append(product_key_W2)
op10_WIP.append(op10_l)
op10_WIP.append(op10_w)
op10_WIP.append(op10_h)
op10_WIP.append(op20_process_time)
op10_WIP.append(datetime.now() + timedelta(hours=9))
# 새 제품 생산
body = []
product_key_W1 = '-' + 'W1' + 'P' + str(i)
body_l = np.random.normal(200, std) # body 치수 데이터 생성
body_l = round(body_l, 5)
body_w = np.random.normal(100, std) # body 치수 데이터 생성
body_w = round(body_w, 5)
body_h = np.random.normal(50, std) # body 치수 데이터 생성
body_h = round(body_h, 5)
op10_time_stamp = datetime.now() + timedelta(hours=9)
body.append(product_key_W1)
body.append(body_l)
body.append(body_w)
body.append(body_h)
body.append(op10_process_time)
body.append(op10_time_stamp) # 시작 시간
time.sleep(10) # 공정 실행
# 공정들 6개 실행
op60_data = machine_operate.op60(op50_WIP)
op50_data = machine_operate.op50(op40_WIP)
op40_data = machine_operate.op40(op30_WIP)
op30_data = machine_operate.op30(op20_WIP)
op20_data = machine_operate.op20(op10_WIP)
op10_data = machine_operate.op10(body)
total_test_data.append(op30_data)
total_test_data.append(op20_data)
total_test_data.append(op10_data)
op10_data = total_test_data.pop(0)
op20_data = total_test_data.pop(0)
op30_data = total_test_data.pop(1)
pred = Predict.predict_quality(op10_data, op20_data, op30_data)
print('P' + str(i - 2) + ' 품질 예측값: ' + str(pred))
MySQL_query.insert_product_prediction(op30_data, op20_data,
op10_data, pred)
now_product = op60_data['product_key']
print('6개 생산 완료! %s 제품이 생산되었습니다.' % (now_product))
return "공정 실행 완료!"
def op10(body):
op10_data = {}
std = 0.0025
product_key = body[0]
wavyfin_l = np.random.normal(100, std)
wavyfin_l = round(wavyfin_l, 5)
wavyfin_w = np.random.normal(50, std)
wavyfin_w = round(wavyfin_w, 5)
wavyfin_h = np.random.normal(60, std)
wavyfin_h = round(wavyfin_h, 5)
op10_electricity = np.random.uniform(89, 100)
op10_electricity = round(op10_electricity, 5)
op10_data['product_key'] = product_key
op10_data['body_l'] = body[1]
op10_data['body_w'] = body[2]
op10_data['body_h'] = body[3]
op10_data['wavyfin_l'] = wavyfin_l
op10_data['wavyfin_w'] = wavyfin_w
op10_data['wavyfin_h'] = wavyfin_h
op10_l = body[1]
op10_data['op10_l'] = op10_l
op10_w = body[2]
op10_data['op10_w'] = op10_w
op10_h = wavyfin_h
op10_data['op10_h'] = op10_h
op10_process_time = body[3]
op10_data['op10_electricity'] = op10_electricity
op10_data['op10_process_time'] = op10_process_time
if (op10_l < 199.99) or (op10_l > 200.01):
length_test = 1
else:
length_test = 0
if (op10_w < 99.99) or (op10_w > 100.01):
width_test = 1
else:
width_test = 0
if (op10_h < 59.99) or (op10_h > 60.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
op10_test = 'OK'
op10_data['op10_test'] = op10_test
else:
op10_test = 'NOK'
op10_data['op10_test'] = op10_test
now = datetime.now()
time_stamp = now + timedelta(seconds=op10_process_time)
op10_data['op10_time_stamp'] = time_stamp
time_stamp = str(time_stamp)
product_key = time_stamp + product_key
# product_history 적재
product_history_data_list = []
product_history_insert = {}
op10_master_data = product_master.op10_WIP(1)
product_code = op10_master_data['product_code']
product_history_insert['product_key'] = product_key
product_history_insert['product_code'] = product_code
product_history_insert['product_timestamp'] = time_stamp
product_history_data_list.append(product_history_insert)
MySQL_query.insert_product_history(product_history_data_list) # 히스토리 데이터 DB 적재
# product_quality 적재
product_quality_data_list = [] # 딕셔너리 데이터 저장할 리스트
product_quality_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
product_quality_insert['product_key'] = product_key
product_quality_insert['product_size_l'] = str(op10_l)
product_quality_insert['product_size_w'] = str(op10_w)
product_quality_insert['product_size_h'] = str(op10_h)
product_quality_insert['product_test'] = str(op10_test)
product_quality_insert['product_test_timestamp'] = str(time_stamp)
product_quality_data_list.append(product_quality_insert)
MySQL_query.insert_product_quality(product_quality_data_list) # 품질 데이터 DB 적재
# machine 적재
machine_data_list = [] # 딕셔너리 데이터 저장할 리스트
machine_data_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
machine_master_data = machine_master.op10(1) # machine_code 가져오기
machine_code = machine_master_data['machine_code']
machine_data_insert['machine_code'] = machine_code
machine_data_insert['product_key'] = product_key
machine_data_insert['start_time'] = str(now)
machine_data_insert['end_time'] = str(time_stamp)
machine_data_insert['makespan'] = '123'
machine_data_insert['process_time'] = str(op10_process_time)
machine_data_insert['machine_data'] = str(op10_electricity)
machine_data_insert['machine_data_code'] = 'E01'
machine_data_list.append(machine_data_insert)
MySQL_query.insert_machine(machine_data_list) # machine 데이터 DB 적재
return op10_data
from SQL import MySQL_query import pandas as pd from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import accuracy_score from sklearn.model_selection import train_test_split machine_data = MySQL_query.get_machine_data_list_for_predict(1) quality_data = MySQL_query.get_quality_data_list_for_predict(1) machine_df = pd.DataFrame(machine_data) quality_df = pd.DataFrame(quality_data) product_key_list = [] body_l_list = [] body_w_list = [] body_h_list = [] wavyfin_l_list = [] wavyfin_w_list = [] wavyfin_h_list = [] op10_l_list = [] op10_w_list = [] op10_h_list = [] pipe1_l_list = [] pipe1_w_list = [] pipe1_h_list = [] op20_l_list = [] op20_w_list = []
def product_master():
product_master_data = []
# EGR Cooler 제품
master_dict = {}
product_name = 'EGR_Cooler'
product_code = 'EGRC' # PK
product_class = 'N01'
product_num = 'P01'
product_target_l = 'op60_l_260'
product_target_w = 'op60_w_180'
product_target_h = 'op60_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# op10 반제품
master_dict = {}
product_name = 'WIP10'
product_code = 'op10_WIP' # PK
product_class = 'N02'
product_num = 'WIP1'
product_target_l = 'op10_l_200'
product_target_w = 'op10_w_100'
product_target_h = 'op10_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# op20 반제품
master_dict = {}
product_name = 'WIP20'
product_code = 'op20_WIP' # PK
product_class = 'N02'
product_num = 'WIP2'
product_target_l = 'op20_l_200'
product_target_w = 'op20_w_140'
product_target_h = 'op20_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# op30 반제품
master_dict = {}
product_name = 'WIP30'
product_code = 'op30_WIP' # PK
product_class = 'N02'
product_num = 'WIP3'
product_target_l = 'op30_l_200'
product_target_w = 'op30_w_180'
product_target_h = 'op30_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# op40 반제품
master_dict = {}
product_name = 'WIP40'
product_code = 'op40_WIP' # PK
product_class = 'N02'
product_num = 'WIP4'
product_target_l = 'op40_l_230'
product_target_w = 'op40_w_180'
product_target_h = 'op40_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# op50 반제품
master_dict = {}
product_name = 'WIP50'
product_code = 'op50_WIP' # PK
product_class = 'N02'
product_num = 'WIP5'
product_target_l = 'op50_l_260'
product_target_w = 'op50_w_180'
product_target_h = 'op50_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# body 부품
master_dict = {}
product_name = 'body_part'
product_code = 'body' # PK
product_class = 'N03'
product_num = 'PART1'
product_target_l = 'body_l_200'
product_target_w = 'body_w_100'
product_target_h = 'body_h_50'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# wavyfin 부품
master_dict = {}
product_name = 'wavyfin_part'
product_code = 'wavyfin' # PK
product_class = 'N03'
product_num = 'PART2'
product_target_l = 'wavyfin_l_100'
product_target_w = 'wavyfin_w_50'
product_target_h = 'wavyfin_h_60'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# pipe1 부품
master_dict = {}
product_name = 'pipe1_part'
product_code = 'pipe1' # PK
product_class = 'N03'
product_num = 'PART3'
product_target_l = 'pipe1_l_30'
product_target_w = 'pipe1_w_50'
product_target_h = 'pipe1_h_30'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# pipe2 부품
master_dict = {}
product_name = 'pipe2_part'
product_code = 'pipe2' # PK
product_class = 'N03'
product_num = 'PART4'
product_target_l = 'pipe2_l_30'
product_target_w = 'pipe2_w_50'
product_target_h = 'pipe2_h_30'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# flange1 부품
master_dict = {}
product_name = 'flange1_part'
product_code = 'flange1' # PK
product_class = 'N03'
product_num = 'PART5'
product_target_l = 'flange1_l_30'
product_target_w = 'flange1_w_50'
product_target_h = 'flange1_h_30'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
# flange2 부품
master_dict = {}
product_name = 'flange2_part'
product_code = 'flange2' # PK
product_class = 'N03'
product_num = 'PART6'
product_target_l = 'flange2_l_30'
product_target_w = 'flange2_w_50'
product_target_h = 'flange2_h_30'
master_dict['product_name'] = product_name
master_dict['product_code'] = product_code # PK
master_dict['product_class'] = product_class
master_dict['product_num'] = product_num
master_dict['product_target_l'] = product_target_l
master_dict['product_target_w'] = product_target_w
master_dict['product_target_h'] = product_target_h
product_master_data.append(master_dict)
MySQL_query.insert_product_master(product_master_data)
return product_master_data
def op60(op50):
op60_data = {}
std = 0.0025
product_key = op50[0]
op60_process_time = op50[4]
op60_l = op50[1]
op60_data['op60_l'] = op60_l
op60_w = op50[2]
op60_data['op60_w'] = op60_w
op60_h = op50[3]
op60_data['op60_h'] = op60_h
op60_data['op60_process_time'] = op60_process_time
if (op60_l < 259.99) or (op60_l > 260.01):
length_test = 1
else:
length_test = 0
if (op60_w < 179.99) or (op60_w > 180.01):
width_test = 1
else:
width_test = 0
if (op60_h < 59.99) or (op60_h > 60.01):
height_test = 1
else:
height_test = 0
if length_test == 0 and width_test == 0 and height_test == 0:
op60_test = 'OK'
op60_data['op60_test'] = op60_test
else:
op60_test = 'NOK'
op60_data['op60_test'] = op60_test
now = op50[5]
time_stamp = now + timedelta(seconds=10)
op60_data['op60_time_stamp'] = time_stamp
time_stamp = str(time_stamp)
product_key = time_stamp + product_key
op60_data['product_key'] = product_key
# product_history 적재
product_history_data_list = []
product_history_insert = {}
op60_master_data = product_master.EGRC(1)
product_code = op60_master_data['product_code']
product_history_insert['product_key'] = product_key
product_history_insert['product_code'] = product_code
product_history_insert['product_timestamp'] = time_stamp
product_history_data_list.append(product_history_insert)
MySQL_query.insert_product_history(
product_history_data_list) # 히스토리 데이터 DB 적재
# product_quality 적재
product_quality_data_list = [] # 딕셔너리 데이터 저장할 리스트
product_quality_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
product_quality_insert['product_key'] = product_key
product_quality_insert['product_size_l'] = str(op60_l)
product_quality_insert['product_size_w'] = str(op60_w)
product_quality_insert['product_size_h'] = str(op60_h)
product_quality_insert['product_test'] = str(op60_test)
product_quality_insert['product_test_timestamp'] = str(time_stamp)
product_quality_data_list.append(product_quality_insert)
MySQL_query.insert_product_quality(
product_quality_data_list) # 품질 데이터 DB 적재
# machine 적재
machine_data_list = [] # 딕셔너리 데이터 저장할 리스트
machine_data_insert = {} # DB 저장할 데이터 모아주는 딕셔너리
machine_master_data = machine_master.op60(1) # machine_code 가져오기
machine_code = machine_master_data['machine_code']
machine_data_insert['machine_code'] = machine_code
machine_data_insert['product_key'] = product_key
machine_data_insert['start_time'] = str(now)
machine_data_insert['end_time'] = str(time_stamp)
machine_data_insert['makespan'] = '123'
machine_data_insert['process_time'] = str(op60_process_time)
machine_data_insert['machine_data'] = str(131.1)
machine_data_insert['machine_data_code'] = 'TEST'
machine_data_list.append(machine_data_insert)
MySQL_query.insert_machine(machine_data_list) # machine 데이터 DB 적재
return op60_data
def count_product_today(self): # 오늘 생산한 양품 갯수 리턴하는 함수
data = MySQL_query.get_item_count_for_gauge()
count_new_product = data[0]['item_count']
return count_new_product
