Job Shop Optimization

1. Job Shop Optimization December 8, 2005 Dave Singletary Mark Ronski

2. Introduction

3. Problem Statement • Open Ended • Optimize a job shop • Utilize Pro Model software to optimize • Cost Model • SimRuner Module

4. Problem Statement (Cont.) • Optimized Model For… • Delivery Schedule • Q Size • Takt Time • Number of Workers

5. Outline • Overview Pro Model • Job Shop Model • Optimization Terms • Results

6. Pro Model Overview

7. Pro Model • Process optimization and decision support software model • Serving: • Pharmaceutical • Healthcare • Manufacturing industries. • Helps companies: • Maximize throughput • Decrease cycle time • Increase productivity • Manage costs.

8. Pro Model Cont… • Pro Model technology enables users to: • Visualize • Analyze • Optimize • Helps make better decisions and realized performance and process optimization objectives.

9. What Pro Model Is… • Create 3-D Simulation of Shop Space • Machines X-Y Coordinates • Time • Alter Machine, Worker, and Cost Parameters to Simulate Outcome • Tools to Optimize Shop Model

10. Pro Model Simulation

11. Job Shop Model

12. MILL Cap.: 1 TURN Cap.: 1 2 ft 2 ft DRILL Cap.: 1 MILL Q Cap.: 90 TURN Q Cap.: 20 0 ft 0 ft GRIND Cap.: 1 RECEIVING Cap.: 150 OUTPUT GRIND Q Cap.: 20 5 ft 15 ft 15 ft 15 ft 2 ft 5 ft 10 ft DEBURR Q Cap.: 80 0 ft DEBURR Cap.1 Key Cap. = Maximum Capacity Default Shop Layout

13. Parts to Be Manufactured • 3 Parts to be Manufactured • 5 Machining Processes • 4 Process Per Part

14. DEBURR 2 min RECEIVE DRILL 7 min MILL 3.66 min DEBURR 2 min OUTPUT GRIND 5.4 min Machining Processes Part N101

15. RECEIVE DRILL 3.6 min TURN 4 min DEBURR 5 min OUTPUT GRIND 2.6 min Machining Process (Cont.) Part N201 DEBURR 7 min

16. DEBURR 2 min RECEIVE MILL 3.8 min TURN 4 min DEBURR 5 min OUTPUT GRIND 1.2 min Machining Process (Cont.) Part N301

17. Machining Process Summary

18. Process Variability • Default Job Shop Model • Constant Setup Time • Constant Machining Time • No Machine Failure • Introduce Variability to Mimic Actual Conditions

19. Process Variability (Cont.) • Normally Distributed… • Setup Time • Machining Time • Machine Failure • Average Time = Default Value • Standard Deviation = ¼ Average Time

20. Normal Distribution • In a normal distribution: • 50% of samples fall between ±0.75 SD • 68.27% of samples fall between ±1 SD • 95.45% of samples fall between ±2 SD • 99.73% of samples fall between ±3 SD Xbar = Mean

21. COST Machine Cost and Life

22. COST Man Power Cost and Initial Part Cost

23. COST Tool Cost, Tool Life, and Hours Down to Change Part

24. Workers • Speed 120 feet per minute • With or Without Carrying a Part • Pick Up or Place Object in 2 seconds • Logic • Stay at Machine Until Q is Empty • Go to Closest Unoccupied Machine • Go to Break Area When Idol

25. Optimization Terminology

26. Takt Time • Takt Time = ratio of available time per period to customer demand. • Longest operation must not exceed Takt time. • If Takt time exceeded customer demand is not met.

27. Kanban Capacity • Kanban = Maximum number of parts allowed between stations • Size of Deburr Q, Mill Q, Drill Q • When Q is full machine prior to Q must shut down • Pull manufacturing controlled by Kanban • Open slot in the Q causes the previous machine to make a part.

28. Kanban Capacity (Cont.) • Each part in Q has value added • Parts in Q are not earning the company money • Increase in Kanban capacity increases production rate. • Upper limit exists

29. Just In Time (JIT) Production • Receive supplies just in time to be used. • Produce parts just in time to be made into subassemblies. • Produce subassemblies just in time to be assembled into finished products. • Produce and deliver finished products just in time to be sold.

30. Optimization and Results

31. Takt Time Optimization • Slowest process must be faster than required Takt time. • Checked if job shop can meet demand of 229 parts per week. • Determines if… • More Machines Required • Faster Machines Required

32. Takt Time for job shop Longest Operation = 7 minutes Drill N101 and Deburr N201 Conclusions: Current machine process times less than Takt time Margin provided for variability and failure. Takt Time Calculations

33. Kanban Capacity Optimization • Default Simulation • Run to Detect Inadequate Kanban Capacity • Optimized Simulation • Smallest Allowable Kanban Capacity Resulted in Q 0% Full Over 1 Month of Production • Run for Default Receiving Delivery Schedule

34. Kanban Capacity Default

35. Optimized Kanban Capacity

36. Delivery Schedule Optimization • Delivery Schedule • The Timed Arrival of Raw Material to Receiving. • Default Simulation • Run to Determine the Effect of Delivery Schedule on Production

37. Default Production Rate Waiting For Parts to Arrive 158 Hours to Make All Parts

38. Delivery Schedule Optimization • Optimized Simulation • Delivery Schedule Altered to Simulate Just in Time Production • All Parts for 4 Weeks Received at Start of Week

39. Optimized Production Rate No Breaks in Production Due to No Parts in Receiving 136 Hours to Make All Parts

40. Delivery Schedule Conclusions • Option 1: 3 Full Time Employees Not Required for Part Demand • Cost Savings • Option 2: Increase Production • Only if Market Demand Will Meet Increased Production

41. Resource Optimization for Max Production • Default Model Setup • 3 Workers • Optimized Model • Maximize Production • Minimize Worker Down Time • Get Maximum Value Out of Workers • During Worker Down Time No Value Added

42. Resource Optimization Model • Pro Model Sim Runner • Optimizes Macro • Varies Number of Workers 1:10 • Maximizes Weighted Optimization Function F • A and B are Weighting Constants • N101, N201, N301is Average Time in System for Each Part • Pworkers = Percent Utilization of Workers (%)

43. Resource Optimization Model (Cont.) • Values of Constants • A = Ave. Time in Sys. Constant • Set Equal to 1 • B = Percent Utilization of Workers Const. • Equal in Importance to Ave. Time in Sys. • Calculating B Through Default Values

44. Resource Optimization Results • Sim Runner Calculated 3 Workers to Optimize Job Shop • Current Default Value • Important Result • Increasing Workers Will Increase Production But Decrease Return on Worker Cost • Must Buy New Machines to Stay Optimized and Increase Production

45. Conclusions

46. Job Shop Optimization • Optimize for Currant Demand • Alter Q Size • Increase Deburr and Mill, Decrease Turning and Grinding • Remove Bottle Necks • Decrease Lost Profits Due to Parts Sitting in System • Switch to Just In Time Production • Decrease Shop Downtime Due to Waiting for Parts

47. Job Shop Optimization (Cont.) • Optimize for Increased Demand • Purchase New Machines • Increase Production Not at the Expense of Worker Utilization • Switch to Just In Time Production • Decrease Shop Downtime Due to Waiting for Parts • Revaluate Takt Time • Ensure Demand Will Be Met

48. Pro Model Recommendation • Sim Runner Difficult to Use • Non Robust Optimization Technique • Difficult to Compare Parameters that have Different Units • Good At Modeling Shop Layout and Work Flow • Easy to Find Bottle Necks

49. Questions ?

50. References • Schroer, Bernard J. Simulation as a Tool in Understanding the Concepts of Lean Manufacturing. University of Alabama: Huntsville. • Gershwin, Stanley B. Manufacturing Systems Engineering. Prentice Hall: New Jersey, 1941. • Kalpakjian, S. and Schmid, R. Manufacturing Engineering and Technology. Fourth Edition, Prentice Hall: New Jersey, 2001.