The Production Scheduling for Job Shop Production in Parallel Machines ABSTRACT

Transcription

1 The Production Scheduling for Job Shop Production in Parallel Machines by Pornkiat Phakdeewongthep College of Logistics and Supply Chain Suan Sunandha Rajabhat University Nakhonpathom Learning Center 111/3-5 Moo 2, Tambon Klongyong Phutthamonthon District Nakhonprthom 73170, Thailand ABSTRACT This research aimed to reduce time of production planning and reduce the delayed jobs by creating a computer program, visual basic 6.0, structure query language (SQL), the barcode system and Heuristic method were used to create this computer program. This company has several kind of products such as mold, jig and fixture, auto parts and machine parts so manufacturing system of this company is job shop production. The planner officers used a lot of time for production scheduling because a job had a lot of processes, outsources and machines so each month had a lot of the delayed jobs. Then, a researcher created computer program, used the barcode system to assist tracking and increase efficient of planning and used application earliest due date (EDD) method for the production scheduling by comparing 4 methods were FIFO, EDD_FIFO, EDD_LPT and EDD_SPT. The results showed that EDD_SPT was the best. When the computer program was used to plan and schedule that could reduce time of production planning 409 minutes per job to 271 minutes per job. Finally, the research could reduce number of the delayed jobs from 52 jobs to 38 jobs. Keywords: Production Scheduling, Job Shop Production, Parallel Machines, Heuristic. 1. INTRODUCTION Currently, Thailand's automotive industry is the industry that the government has provided facility. The government s the goal want to consistently promote Thailand as a hub for automotive production and export. Results of action in this approach, Thailand's automotive industry is growing continuously. The last development of the automotive industry has found, it is focused on low-cost production and the quality production that are a key factor for the competition. Cars are produced more variety, the shape color technology and the price. For the big manufacturers are TOYOTA, HONDA, NISSAN, FORD and others. They develop cars all time to be able to meet the needs of customers that have changed over time. Manufacturers of mold parts must prepare everything to support the expansion by planning to use manpower machines raw materials and the production scheduling. If the mold parts manufacturer cannot deliver goods on time, it will impact the delivery of the big manufacturers.

2 The production planning in each time need to use a lot of basic information required and updated information such as specific information, drawing, delivery date, quantity, available machine, material information, the sequenced process, job status in process, tool for quality control, packing, testing, etc. If planner takes a long time to receive this information, then production scheduling will take a long time as well. Finally, the company will have a lot of the delayed jobs. The foregoing, the time is very important for planning each time. Another important thing is job sequencing in each machine. That is, when have a lot of jobs to plan in a machine, job sequencing is very important. If planner sequence inefficient, it causes problems in delayed delivery. When a factory had the delayed delivery delay, the receiver would be affected. The receiver must change process modal, time modal, transportation model, packaging modal and others for the delayed product was sent to consumer on time (Duangjai Jandasang, Wannee Sutthachaidee,. 2015). The factory is a small and medium enterprise (SME) and has several kinds of products such as mold, jig and fixture, auto parts and machine parts. The results of study showed that a factory had a lot of delayed jobs that is shown in table 1. Table 1 The percentage of the delayed jobs from January, 2012 to June, Month Total jobs Delayed job The percentage of the delayed job January February March April May June From table 1, the analysis of the causes of delayed delivery (Pornkiat Phakdeewongthep and Pairoj Raothanachonkun, 2012) that had three steps. First, a basic analysis by the Quick Scan was used to analyze for cutting out irrelevant departments. Later, an advanced analysis by Supply Chain Operations Reference Model (SCOR Model) was used to analyze for showing details of delayed delivery. Finally, a depth analysis by Why-Why Analysis was used to analyze for showing root cause of delayed delivery (Danai Aphiraksanti, 2013). The results showed that delayed delivery of this factory had root cause at planning department. A root cause was planner used a lot of time for production scheduling because planner used a lot of time to find information for production scheduling and production scheduling was difficult because process was job shop. The case when there were a lot of assembly jobs, a factory will have a lot of quantity of delayed jobs that is shown in table 2 because an assembly job had about 150 sub-jobs and job scheduling was difficult than normal jobs

3 Table 2 Assembly job ratio Month Delayed job rmal job Assembly job The percentage of assembly job January February March April May June Used the time to find the information too long. had a lot of sub jobs too many. Machine group 1 Machine group n could not track the status of all. Outsourcing Finding information problem Assembly problem Sequencing problem Figure 1 All problems of planning Tracking problem Therefore, from table 2 and figure 1, this research aimed to: (1) reduce time for production planning (Suthathip Budsaba, 2011) and (2) reduce quantity of delayed jobs (Kridsada Chawbangprom, 2011) by creating a computer program that visual basic 6.0, structure query language (SQL), the barcode system and Heuristic method were used to create this computer program (Wirote Pintaruk, 2010). Information was used for production scheduling. 2. LITERATURE REVIEW Kanate (2011) conducted a study of algorithm development for solving flexible job shop scheduling problem by genetic algorithm (GA), particle swarm optimization (PSO) and the Makespan Tree. There were 2 steps. First, jobs must be assigned to machines. Second, jobs must be sequenced. The results for this research showed that the Makespan Tree had the shortest process time was 57.41% Pongtada (2013), this study was comparison unrelated parallel machines scheduling of result from scheduling program and assignment problem. The purpose of this thesis was the studying production scheduling and increasing the efficiency of job scheduling by using computer program and comparison method, Earliest Due Date (EDD), Minimum Slack Time (MS), First Come First Served (FCFS), Longest Processing Time (LPT) and Shortest Processing Time (SPT). The results for this research showed that EDD had the minimum of tardiness and number of late jobs. Rukkiat (2012) studied of multi-objective scheduling and sequencing, a case study of a plastic injection factory. This research aimed to solve tardiness problem by comparison 15 scheduling (EDD, LWKR, MWKR, MOPNR, SMT, SPT, STPT, LWKT (with setup time), MWKR (with setup time), MOPNR (with setup time), SMT (with setup time), SPT (with setup time), STPT (with setup time), Heuristic1, Heuristic1 and Heuristic3). The results for this research showed that Heuristic2 was used and the percentage of tardiness reduced from 17.85% to 0%. Sakorn (2013) studied of production scheduling of pressing process for automobile by using Heuristic method. This research aimed to create production scheduling and the minimum delayed job

4 by comparison Shortest Processing Time (SPT), Longest Processing Time (LPT), Earliest Deadline First (EDF) and Least Slack Time First (LSTF). The results for this research showed that EDF did not have delayed job. Sarwitee (2013), this research was the study of production scheduling of printer machine in plastic packaging. This research aimed to develop job scheduling algorithm by using the mathematical model of the production scheduling and Excel solver. The mathematical models were used this research that had Shortest Processing Time (SPT) and Longest Processing Time (LPT). The results for this research showed that SPT was the best. The makespan time was reduced from 4,500 minutes to 3,066 minutes. The mean flow time was reduced from minutes to minutes. The total time was reduced from 27,000 minutes to 18,382 minutes. 3. RESEARCH METHODOLOGY 3.1 Population and Sample Population and sample size had 30 employees. A factory is in Pathum Thani province, Thailand. 3.2 Planning improvements Planning improvements aimed to reduce time for production planning and reduce quantity of delayed jobs. There were 2 parts: (1) the study the information and (2) designing program The study the information The study the information was used for production scheduling by the study the Work Instruction (WI), the study the actual work and interviewing staff, supervisor and manager. The results of study were used for designing the program Designing program The program was designed that it had multiple functions to: (1) connected information for production planning; (2) supported Bar Codes to be used to track jobs; (3) printed reports such as delivery report, backlogs report, etc. and (4) scheduled jobs by application Heuristic method to reduce quantity of delayed jobs. From the reviewing researches showed that job scheduling by Earliest Due Date (EDD) (Yodduangjai Nakpathom, 2012) was most effective to reduce delayed jobs, so this research had the scope application of EDD for job scheduling case assembly job, job shop production in parallel machines, 27 machines and 11 machine groups.

5 3.3 Heuristic Method Heuristic method for assembly job had 2 parts: (1) job scheduling and (2) finding the arrival time and completion time Job scheduling Job scheduling for assembly job by application Heuristic method to reduce quantity of delayed jobs. Heuristic method could not be used directly because an assembly job had about 150 sub-jobs that some sub jobs will be done only when other sub jobs were completed. Therefore, this research has 4 test methods were First Come First Serve (FCFS), Earliest Due Date and First Come First Serve (EDD_FCFS), Earliest Due Date and Longest Processing Time (EDD_LPT) and Earliest Due Date and Shortage Processing Time (EDD_SPT). 1. First Come First Serve (FCFS) was job sequencing by the first arrival job will be done that is shown in figure 2. Currently, the factory used this method to sequencing. Start Assembly job Job scheduling for normal job Job scheduling for assembly job Sub jobs Do not have Have Choose sub job Sort arrival date form low to high All sub jobs are done Finish Figure 2 First Come First Serve (FCFS) for assembly job 2. Earliest Due Date and First Come First Serve (EDD_FCFS) was job sequencing by sorting delivery dates from low to high. If jobs had same delivery date, the first arrival job will be done that is shown in figure 3.

6 Start Assembly job Job scheduling for normal job Job scheduling for assembly job Sub jobs Do not have Have Choose sub job Sort delivery date form low to high Same delivery date Sort arrival date form low to high All sub jobs are done Finish Figure 3 Earliest Due Date and First Come First Serve (EDD_FCFS) for assembly job 3. Earliest Due Date and Longest Processing Time (EDD_LPT) was job sequencing by sorting delivery dates from low to high. If jobs had same delivery date, the longest time job will be done that is shown in figure 4.

7 Start Assembly job Job scheduling for normal job Job scheduling for assembly job Sub jobs Do not have Have Choose sub job Sort delivery date form low to high Same delivery date Sort process time form high to low All sub jobs are done Finish Figure 4 Earliest Due Date and Longest Processing Time (EDD_LPT) for assembly job 4. Earliest Due Date and Shortage Processing Time (EDD_SPT) was job sequencing by sorting delivery dates from low to high. If jobs had same delivery date, the shortest time job will be done that is shown in figure 5.

8 Start Assembly job Job scheduling for normal job Job scheduling for assembly job Sub jobs Do not have Have Choose sub job Sort delivery date form low to high Same delivery date Sort process time form low to high All sub jobs are done Finish Figure 5 Earliest Due Date and Shortage Processing Time (EDD_SPT) for assembly job The finding the arrival time and the completion time The finding the arrival time and the completion time for assembly job by comparison the arrival time and the completion time of processes and machines. There were 6 steps. 1. Step1: Start to schedule jobs by selecting a method. Then, set 2 parameters are JOB_Process_ID and JOB_Seq. Later, find arrival time1 (Ai1) and completion time1 (Ci1) of all jobs. Finally, record Ai1 and Ci1 that is shown in figure 6 and table 3. Step1 Scheduled jobs by Heuristic method Set JOB_Process_ID, JOB_Seq Find Arrival time1 (Ai1) and completion time1 (Ci1) all jobs Time1 = Ai1, Ci1 Step2 Figure 6 Flowchart of step 1

9 Table 3 Example of Step 1 EDD Ai1 Ci1 JOB_DESC DELIVERLY_DATE JOB_PROCESS_ID JOB_PROCESS_NAME JOB_Seq Process_Time Due_Time Start_Time Finish_Time /1/ CT /1/ CL /1/ QC /1/ HE /1/ CL /1/ QC /1/ CO /1/ QC(F) /3/ CT /3/ CL /3/ QC /3/ HE /3/ CL /3/ QC /3/ CO /3/ QC(F) Step2: Start to sort JOB_Process_ID from low to high. Then, find arrival time2 (Ai2) and completion time2 (Ci2) of all process. Finally, record Ai2 and Ci2 that is shown in figure 7 and table 4. Step2 Sort JOB_Process_ID from low to high Find Arrival time2 (Ai2) and completion time2 (Ci2) all process Time2 = Ai2, Ci2 Step3 Figure 7 Flowchart of step 2 Table 4 Example of Step 2 EDD Ai1 Ci1 Time2 JOB_DESC JOB_PROCESS_ID JOB_PROCESS_NAME JOB_Seq Process_Time Due_Time Start_Time Finish_Time Ai2 Ci CT CT Step3: Start to compare Ci2 with Ai1 and all process. Then find Ai3 and Ci3. Finally, record Ai3 and Ci3 that is shown in figure 8 and table 5.

10 Step3 Ci2 > Ai1 Ai3 = Ai1 Ai3 = Ci2 of before process Ci3 = Ai3 + Process_ Time Time3 = Ai3, Ci3 Step4 Figure 8 Flowchart of step 3 Table 5 Example of Step 3 Ai1 Ci1 Time3 JOB_DESC JOB_PROCESS_ID JOB_PROCESS_NAME JOB_Seq Process_Time Start_Time Finish_Time Ai2 Ci2 Ai3 Ci CT CL QC HE CL QC CO QC(F) CT CL QC HE CL QC CO QC(F) Step4: Start to set Qty_MC, MC_NO, MC_NAME and MC_Loop. Then sort JOB_Process_ID from low to high. Finally, put name machine to JOB_Process_ID that is shown in figure 9 and table 6.

11 Step4 Set Qty_MC, MC_NO, MC_NAME, MC_Loop Sort JOB_Process_ID from low to high Qty_MC > 1 MC_NAME = Machine1 MC_NAME = Machine1 for job1 MC_NAME = Machine n for job n JOB_Process_ID +1 End JOB_Process_ID Step5 Figure 9 Flowchart of step 4 Table 6 Example of Step 4 JOB_DESC JOB_PROCESS_ID JOB_PROCESS_NAME Qty_MC Process_Time Ai3 Ci3 MC_NO MC_NAME MC_Loop CT CL MCL QC HE CL MCL QC CO QC(F) CT CL MCL QC HE CL MCL QC CO QC(F) Step5: Start to choose JOB_PROCESS_NAME. Then find Ai4 and Ci4. Finally, record Ai4 and Ci4 that is shown in figure 10 and table 7.

12 Step5 Choose JOB_PROCESS_NAME Find Arrival time4 (Ai4) and completion time4 (Ci4) all machines Time4 = Ai4, Ci4 Step6 Figure 10 Flowchart of step 5 Table 7 Example of Step 5 JOB_DESC JOB_PROCESS_ID JOB_PROCESS_NAME Qty_MC Ai3 Ci3 MC_NO MC_NAME Ai4 Ci CL MCL CL MCL CL MCL CL MCL Step6: Start to compare Ai3 with Ci4, if there are same MC_NAME. Then find Ai5 and Ci5. Finally, record Ai5, Ci5 and transfer them to date that is shown in figure 11 and table 8. Step6 Same MC_NAME Ai3 > Ci4 of before process Ai5 = Ci4 of before process Ai5 = Ai3 Ci5 = Ai4 + Process_ Time Time5 = Ai5, Ci5 Transfer Time5 to date Finish Figure 11 Flowchart of step 6

13 Table 8 Example of Step 6 JOB_DESC JOB_PROCESS_NAME Qty_MC Ai3 Ci3 Ai4 Ci4 Ai5 Ci CT CL QC HE CL QC CO QC(F) CT CL QC HE CL QC CO QC(F) Performance measurement Performance measurement of program to measure: (1) the time was used for production scheduling by starting to receive customer order process until to deliver products process and (2) delayed jobs by comparison each Heuristic method with method of a factory. 4. RESULTS 4.1 The results of planning improvements The results of planning improvements showed that there were 2 parts: (1) the results of the study the information; (2) the results of designing program The results of the study the information The results of the study the information for assembly job showed that there were 7 information were used for production scheduling. Information was: (1) customer requirement; (2) material; (3) drawing; (4) machine; (5) process; (6) process time and (7) job status. 1. Customer requirement for an assembly job was data from the customer orders such as product name, quantity, delivery date, etc. 2. Material for an assembly job was kind of material such as code SKD61, S50C, SKS3, etc. rmally, purchasing department had mixed systems between make to order with make to stock. 3. Drawing for an assembly job had about 150 sub jobs. Assembly job had both rough parts and fine parts. Rough parts had the error more than mm. Rough parts had the error did between mm. that is shown in figure 12.

14 Figure 12 Drawing of assembly job 4. Machine for an assembly job had 27 machines and 11 machine groups that are shown in table 9. Table 9 Machines list Machine Groups Quantity Manual Lathe 2 CNC Lathe 7 Manual Milling 3 CNC Milling 4 Rough Milling 1 Sphere Grinding 3 Small Horizontal Grinding 1 Medium Horizontal Grinding 1 Internal Grinding 2 Radial 1 Cutting 1 5. Process for an assembly job was used for job scheduling. A sub job had about 8 processes. Processes had both internal process and external process such as cutting, roughing, milling, heat treatment, coating, etc. 6. Process time for an assembly job was used for job scheduling. rmally, process time was written minute form such as cutting (50 min.), roughing (90 min.), milling (120 min.), heat treatment (480 min.), coating (960 min.), etc. 7. Job status for an assembly job had 2 statuses: (1) finished and (2) did not finish. If status did not finish, planner must estimate time again such as cutting (finished), roughing (finished), milling (60 min.), heat treatment (480 min.), coating (960 min.), etc.

15 4.1.1 The results of designing program The results of designing program that it had multiple functions such as connecting information, supporting Bar Code to be used to track jobs, printing reports, job scheduling, etc. They are shown in figure 13, figure 14, figure 15, figure 16 and figure 17. Figure 13 Screen for inputting data Figure 14 Screen for inputting process and setting standard process

16 Figure 15 Screen for application Bar code Figure 16 Example of reports Figure 17 Screen for application Heuristic method

17 4.2 The results of application Heuristic method This research had 4 test methods were First Come First Serve (FCFS), Earliest Due Date and First Come First Serve (EDD_FCFS), Earliest Due Date and Longest Processing Time (EDD_LPT) and Earliest Due Date and Shortage Processing Time (EDD_SPT) are shown in table 10, table 11, and table 12. Table 10 Example of EDD_FIFO JOB NO PLAN DATE DELIVERLY_DATE PROCESS_NAME Machine Start Date Finish Date August August-12 CT MC-C-001 2/8/2012 9:00 2/8/2012 9: August August-12 CL MC-L-001 2/8/2012 9:10 2/8/2012 9: August August-12 LA MC-L-005 2/8/2012 9:40 2/8/ : August August-12 QC QC-Tooling 2/8/ :10 2/8/ : August August-12 HE Outsource-HE 2/8/ :20 7/8/ : August August-12 CL MC-L-004 7/8/ :20 7/8/ : August August-12 QC QC-Tooling 7/8/ :20 7/8/ : August August-12 CO Outsource-CO 7/8/ :40 10/8/ : August August-12 CT MC-C-001 2/8/2012 9:10 2/8/2012 9: August August-12 CL MC-L-002 2/8/2012 9:20 2/8/2012 9: August August-12 LA MC-L-009 2/8/2012 9:50 2/8/ : August August-12 QC QC-Tooling 2/8/ :20 2/8/ : August August-12 HE Outsource-HE 2/8/ :30 7/8/ : August August-12 CL MC-L-001 7/8/ :30 7/8/ : August August-12 QC QC-Tooling 7/8/ :40 7/8/ : August August-12 CO Outsource-CO 7/8/ :00 10/8/ :00 Table 11 Example of EDD_LPT JOB NO DELIVERLY_DATE Total_Time Process_Time Machine Start Date Finish Date August MC-C /8/ :00 12/8/ : August MC-L /8/ :30 17/8/ : August MC-M /8/ :30 18/8/ : August MC-M /8/2012 9:50 24/8/ : August QC-Tooling 24/8/ :10 24/8/ : August Outsource-HE 24/8/ :50 29/8/ : August MC-L /8/ :50 31/8/ : August QC-Tooling 15/9/ :54 15/9/ : August MC-M /8/ :00 18/8/ : August QC-Tooling 24/8/ :30 24/8/ : August Outsource-HE 24/8/ :40 29/8/ : August MC-G-005 3/9/ :20 4/9/ : August MC-M-003 4/9/ :20 5/9/2012 9: August MC-L-007 5/9/ :20 6/9/ : August QC-Tooling 8/9/ :14 8/9/ :34

18 Table 12 Example of EDD_SPT JOB NO DELIVERLY_DATE Total_Time Process_Time Machine Start Date Finish Date August MC-M /8/ :00 18/8/ : August QC-Tooling 24/8/ :30 24/8/ : August Outsource-HE 24/8/ :40 29/8/ : August MC-G-005 3/9/ :20 4/9/ : August MC-M-003 4/9/ :20 5/9/2012 9: August MC-L-007 5/9/ :20 6/9/ : August QC-Tooling 8/9/ :14 8/9/ : August MC-C /8/ :00 12/8/ : August MC-L /8/ :30 17/8/ : August MC-M /8/ :30 18/8/ : August MC-M /8/2012 9:50 24/8/ : August QC-Tooling 24/8/ :10 24/8/ : August Outsource-HE 24/8/ :50 29/8/ : August MC-L /8/ :50 31/8/ : August QC-Tooling 15/9/ :54 15/9/ : Results of performance measurement Time The results of comparison time between the current operating with program that is shown in table 13. Table 13 Comparison time between the current operating with program Sequence Procedure The current (minutes / job) Program (minutes / job) 1 Received order Inspected order Checked capacity Recorded order Sent orders to planning department Did production scheduling Adjusted production scheduling Copied production scheduling Sent orders to production department Checked jobs status Reported products to transport department Delivered products Total Time Delayed job The results of comparison delayed jobs each Heuristic method between the current operating with program that is shown in table 14.

19 Table 14 Comparison delayed jobs between the current operating with program Method Total jobs Delayed job The percentage of the delayed job FIFO EDD_FIFO EDD_LPT EDD_SPT CONCLUSION This research aimed to reduce time of production planning and reduce the delayed jobs by creating a computer program, visual basic 6.0, structure query language (SQL), the barcode system and Heuristic method were used to create this computer program. The results showed. 1. From table 13, the results of comparison time between the current operating with program that using program could reduce time operating from 409 minutes per job to 271 minutes per job; the percentage of reducing was From table 14, the results of comparison delayed jobs between the current operating with program that using EDD_SPT program was the best and could reduce delayed jobs from 52 jobs to 38 jobs, the percentage of reducing was REFERENCES Aphiraksanti, Danai (2013). Job Scheduling on n-identical Parallel Printing Machines in Pharmaceutical Industry, King Mongkut s University of Technology Thonburi. Budsaba, Suthathip (2011). The Production Scheduling Generation with Heuristic Methods: Case Study VIP Hat Co.,TH., Silpakorn University. Chaivohan, Sakorn (2013). Production Scheduling of Pressing Process for Automobile Seat Frame Components, King Mongkut s University of Technology Thonburi. Chawbangprom, Kridsada (2011). Decision Support System for Master Production Scheduling and Material Requirement Planning: A Case Study of Flavor Squid Factory, National Institute of Development Administration. Jandasang, Duangjai (2015). Factors Affecting the Service of Transportation use Outbound Freight: Case study of Operators, Ph.D in Social Science journal, 5(3) Kurukidcumchorn, Pongtada (2013). Comparison Unrelated Parallel Machines Scheduling of Result From Scheduling Program and Assignment Problem, Silpakorn University. Nakpathom, Yodduangjai (2012). A Study of Job Shop Production Scheduling on Textile Industry, Silpakorn University.

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