1. MEHMET TANLAK Constraint Management For Operations Management, 9e by Krajewski/Ritzman/Malhotra © 2010 Pearson Education PowerPoint Slides by Jeff Heyl

4. Theory of Constraints An increase in U at the bottleneck leads to an increase in net profit, ROI, and cash flows. The degree to which equipment, space, or workforce is currently being used, and is measured as the ratio of average output rate to maximum capacity, expressed as a percentage Utilization (U) A decrease in OE leads to an increase in net profit, ROI, and cash flows. All the money a system spends to turn inventory into throughput Operating Expense (OE) An increase in T leads to an increase in net profit, ROI, and cash flows. Rate at which a system generates money through sales Throughput (T) A decrease in I leads to an increase in net profit, ROI, and cash flow. All the money invested in a system in purchasing things that it intends to sell Inventory (I) Relationship to Financial Measures TOC View Operational Measures TABLE 7.1 | HOW THE FIRM’S OPERATIONAL MEASURES RELATE TO ITS | FINANCIAL MEASURES

5. Theory of Constraints 7. Every capital investment must be viewed from the perspective of its global impact on overall throughput (T), inventory (I), and operating expense (OE). 6. Activating a nonbottleneck resource (using it for improved efficiency that does not increase throughput) is not the same as utilizing a bottleneck resource (that does lead to increased throughput). Activation of nonbottleneck resources cannot increase throughput, nor promote better performance on financial measures outlined in Table 7.1. 5. Work, which can be materials, information to be processed, documents, or customers, should be released into the system only as frequently as the bottlenecks need it. Bottleneck flows should be equal to the market demand. Pacing everything to the slowest resource minimizes inventory and operating expenses. 4. Inventory is needed only in front of the bottlenecks in order to prevent them from sitting idle, and in front of assembly and shipping points in order to protect customer schedules. Building inventories elsewhere should be avoided. 3. An hour lost at a bottleneck or a constrained resource is an hour lost for the whole system. In contrast, an hour saved at a nonbottleneck resource is a mirage because it does not make the whole system more productive. 2. Maximizing the output and efficiency of every resource may not maximize the throughput of the entire system. 1. The focus should be on balancing flow, not on balancing capacity. TABLE 7.2 | SEVEN KEY PRINCIPLES OF THE THEORY OF CONSTRAINTS

9. Identifying the Bottleneck Figure 7.1 – Processing Credit Loan Applications at First Community Bank Which single step is the bottleneck? The management is also interested in knowing the maximum number of approved loans this system can process in a 5-hour work day. Complete paperwork for new loan (10 min) Check for credit rating (15 min) Enter loan application into the system (12 min) Categorize loans (20 min) Check loan documents and put them order (15 min)

13. Application 7.1 a. For Type A customers, step T2 can process (60/13) = 4.62 customers per hour. T3 has three work stations and a capacity of (60/14) + (60/10) + (60/11) = 15.74 customer per hour. Step T4 can process (60/18) = 3.33 customers per hour. The bottleneck for type A customers is the step with the highest processing time per customer, T4. T1 (12) T7 (10) T4 (18) T3-a (14) T3-c (11) T3-b (10) Type A or B? Type A Type B T2 (13) T6 (22) T5 (15)

14. Application 7.1 b. The bottleneck for Type B customers is T6 since it has the longest processing time per customer. The capacity for Type B customers is (60/22) = 2.73 customers per hour. Thus the average capacity is 0.3(3.33) + 0.7(2.73) = 2.9 customers per hour T1 (12) T7 (10) T4 (18) T3-a (14) T3-c (11) T3-b (10) Type A or B? Type A Type B T2 (13) T6 (22) T5 (15)

15. Application 7.1 before T2 and T4 because the activities immediately preceding them have a higher rate of output. c. Type A customers would wait before steps T5 and T6 for the same reason. This assumes there are always new customers entering the shop. Type B customers would wait T1 (12) T7 (10) T4 (18) T3-a (14) T3-c (11) T3-b (10) Type A or B? Type A Type B T2 (13) T6 (22) T5 (15)

17. Identifying the Bottleneck Figure 7.2 Flowchart for Products A, B, C, and D Product A $5 Raw materials Purchased parts Product: A Price: $75/unit Demand: 60 units/wk Step 1 at workstation V (30 min) Finish with step 3 at workstation X (10 min) Step 2 at workstation Y (10 min) $5 Product C Raw materials Purchased parts Product: C Price: $45/unit Demand: 80 units/wk Finish with step 4 at workstation Y (5 min) Step 2 at workstation Z (5 min) Step 3 at workstation X (5 min) Step 1 at workstation W (5 min) $2 $3 Product B Raw materials Purchased parts Product: B Price: $72/unit Demand: 80 units/wk Finish with step 2 at workstation X (20 min) Step 1 at workstation Y (10 min) $3 $2 Product D Raw materials Purchased parts Product: D Price: $38/unit Demand: 100 units/wk $4 Step 2 at workstation Z (10 min) Finish with step 3 at workstation Y (5 min) Step 1 at workstation W (15 min) $6

19. Identifying the Bottleneck Z Y X W V Total Load (min) Load from Product D Load from Product C Load from Product B Load from Product A Workstation

20. Identifying the Bottleneck These calculations show that workstation X is the bottleneck, because the aggregate work load at X exceeds the available capacity of 2,400 minutes per week. 1,800 0 0 0 60  30 = 1800 1,900 100  15 = 1,500 80  5 = 400 0 0 1,400 100  10 = 1,000 80  5 = 400 0 0 2,300 100  5 = 500 80  5 = 400 80  10 = 800 60  10 = 600 2,600 0 80  5 = 400 80  20 = 1,600 60  10 = 600 Z Y X W V Total Load (min) Load from Product D Load from Product C Load from Product B Load from Product A Workstation

22. Application 7.2 Flowchart for Products A, B, and C Product B Raw materials Purchased part Product: B Price: $85/unit Demand: 70 units/wk Finish with step 4 at workstation Z (13 min) Step 2 at workstation W (10 min) Step 3 at workstation Y (10 min) Step 1 at workstation X (12 min) $9 $5 Product A Raw materials Purchased part Product: A Price: $90/unit Demand: 65 units/wk Finish with step 4 at workstation Z (16 min) Step 2 at workstation Y (15 min) Step 3 at workstation X (9 min) Step 1 at workstation W (10 min) $7 $6 Product C Raw materials Purchased part Product: C Price: $80/unit Demand: 80 units/wk Finish with step 4 at workstation Z (10 min) Step 2 at workstation X (10 min) Step 3 at workstation W (12 min) Step 1 at workstation Y (5 min) $10 $5

24. Application 7.2 Z Y X W Total Load (minutes) Load from Product C Load from Product B Load from Product A Work Station

35. Determining the Product Mix Contribution margin per minute Time at bottleneck Contribution margin Product D Product C Product B Product A

44. Application 7.3 Step 2: Allocate resources W, X, Y, and Z to the products in the order decided in step 1. Satisfy each demand until the bottleneck resource (workstation Z) is encountered. Subtract minutes away from 2400 minutes available for each week at each stage. Z Y X W Can Only Make 45 C After 70 B After 65 A Starting Work Center

45. Application 7.3 Step 2: Allocate resources W, X, Y, and Z to the products in the order decided in step 1. Satisfy each demand until the bottleneck resource (workstation Z) is encountered. Subtract minutes away from 2400 minutes available for each week at each stage. The best product mix is 65 A, 70 B, and 45 C 510 1050 1750 2400 525 975 1815 2400 0 450 1360 2400 500 725 1425 2400 Z Y X W Can Only Make 45 C After 70 B After 65 A Starting Work Center

46. Application 7.3 Step 3: Compute profitability for the selected product mix. Profit Labor Overhead Materials Revenue Profits

47. Application 7.3 Step 3: Compute profitability for the selected product mix. Manufacturing the product mix of 65 A, 70 B, and 45 C will yield a profit of $2980. Profit Labor Overhead Materials Revenue Profits $15400 – $2500 $2980 – $1920 – $8000

50. Application 7.3 Step 2: Allocate resources W, X, Y, and Z to the products in the order decided in step 1. Satisfy each demand until the bottleneck resource (workstation Z) is encountered. Subtract minutes away from 2400 minutes available for each week at each stage. Z Y X W Can Only Make 43 A After 70 B After 80 C Starting Work Center

51. Application 7.3 Step 2: Allocate resources W, X, Y, and Z to the products in the order decided in step 1. Satisfy each demand until the bottleneck resource (workstation Z) is encountered. Subtract minutes away from 2400 minutes available for each week at each stage. The best product mix is 43A, 70B, and 80C 310 740 1440 2400 373 760 1600 2400 2 690 1600 2400 655 1300 2000 2400 Z Y X W Can Only Make 43 A After 70 B After 80 C Starting Work Center

52. Application 7.3 Step 3: Compute profitability for the selected product mix. The new profitability figures are shown below based on the new production quantities of 43A, 70B, and 80C. Profit Labor Overhead Materials Revenue Profits

53. Application 7.3 Step 3: Compute profitability for the selected product mix. The new profitability figures are shown below based on the new production quantities of 43A, 70B, and 80C. Manufacturing the product mix of 43 A, 70 B, and 80 C will yield a profit of $3561. Profit Labor Overhead Materials Revenue Profits $16220 – $2739 $3561 – $1920 – $8000

55. Drum-Buffer-Rope Systems Figure 7.3 – Drum-Buffer-Rope Systems Buffer Drum Market Demand 650 units/wk Shipping Schedule Rope Shipping Buffer Finished Goods Inventory Nonconstraint PROCESS C Capacity 700 units/wk PROCESS B Capacity 800 units/wk CCR (Bottleneck) Constraint Buffer Time Buffer Inventory Nonconstraint PROCESS A Capacity 800 units/wk Material Release Schedule

66. Finding a Solution Picking the candidate with the fewest followers is the opposite of the most followers rule. Fewest followers When picking the next work element to assign to a station being created, choose the element that has the most followers (due to precedence requirements). In Figure 7.4, item C has three followers (F, G, and I) whereas item D has only one follower (H). This rule seeks to maintain flexibility so that good choices remain for creating the last few workstations at the end of the line. Most followers This rule is the opposite of the longest work element rule because it gives preference in workstation assignments to those work elements that are quicker. It can be tried because no single rule guarantees the best solution. It might provide another solution for the planner to consider. Shortest work element Picking the candidate with the longest time to complete is an effort to fit in the most difficult elements first, leaving the ones with short times to “fill out” the station. Longest work element Logic Decision Rule 1. All of their predecessors have been assigned to this station or stations already created. 2. Adding them to the workstation being created will not create a workload that exceeds the cycle time. Create one station at a time. For the station now being created, identify the unassigned work elements that qualify for assignment: They are candidates if TABLE 7.3 | HEURISTIC DECISION RULES IN ASSIGNING THE NEXT WORK ELEMENT TO A | WORKSTATION BEING CREATED

83. Solved Problem 2 S5 S4 S3 S2 S1 Idle Time (c= 150 sec) Cumulative Time (sec) Work-Element Time (sec) Choice Candidate(s) Station J 115 C 30 D 25 E 20 F 15 I 130 H 145 B 80 G 120 A 40

84. Solved Problem 2 J 115 C 30 D 25 E 20 F 15 I 130 H 145 B 80 G 120 A 40 110 40 40 A A 30 120 80 B B 5 145 25 D D, E, F 5 145 115 J J 120 30 30 C C 5 145 15 F F 20 130 130 I F, I 5 145 145 H F, H 10 140 20 E E, F 30 120 120 G E, F, G S5 S4 S3 S2 S1 Idle Time (c= 150 sec) Cumulative Time (sec) Work-Element Time (sec) Choice Candidate(s) Station