1. P RODUCTS P LANNING AND P ROCESS S ELECTION Beni Asllani University of Tennessee at Chattanooga Prepared by Şevkinaz Gümüşoğlu using different references about POM using different references about POM

2. F UTURE P RODUCTS 5-2 Copyright 2006 John Wiley & Sons, Inc.

3. N EW P RODUCT D ESIGN : F UTURISTIC CONCEPT ; DRIVERLESS CAR TECHNOLOGY YOUTUBE. COM / WATCH ? V =V FB JYW R XS9I YOUTUBE. COM / WATCH ? V = CDG Q PA 1 P UUE 5-3 Copyright 2006 John Wiley & Sons, Inc.

4. HTTP :// WWW. WIMP. COM / DRIVERLESSCAR / HTTP :// OBSERVER. COM /2015/01/ MERCEDES - BENZS - NEW - CAR - IS - DRIVERLESS / 5-4 Copyright 2006 John Wiley & Sons, Inc.

5. SONY’ S SMART BANDS, WALKMANZX 2 5-5 Copyright 2006 John Wiley & Sons, Inc.

6. 5-6 Planning new products and geting them to market quickly is the challenge facing manufacturers in industries. In our changing world today customers demand that a company’s offerings be individualized to meet particular meets, situations and lifestyles. They want product and services of superior quality available promptly. The firms requirements are innovation, flexibility, improvement, new practical competencies, design and redesign ways. They must orientate themselves to their customers in a new way.

7. Management must developed and meet the customer’s need by using the available resources and the technological capabilities of the organization. New-product design is crucial to the survival of most firms. While a few firms experience little product change, most firms must continually revise their products. In fast- changing industries, new-product introduction is a way of life and highly sophisticated approaches have been developed to introduce new product. Product design is seldom the responsibility of operations functions but operations is greatly affected by new-product introduction. Sometime, new products are constrained by existing operations and technology. 5-7.

8. Therefore, it is extremely important to understand the new product design process and its interactions with operations. Product decisions affect each of the decision making areas of operations. Therefore they should be closely coordinated with operations to ensure the operation is integrated with production design. There are three strategies for new-product introduction process: 5-8

9. Market-driven: According to this view, “You should make what you can sell” In this case, new products are determined by the market with little regard to existing technology and operations process. Customer needs are the primary basis for new-product introduction. Customer want products and services of superior quality available promptly. The requirements are for innovation, flexibility, quality based on active listening to customer so as to determine their concerns. Being prepared to deliver on such requirements will require companies to cultivate new practical competencies, to redesign the ways they do their work through business processes and to orient themselves to their customers in a new way. (kano system- voice of costumer) Technology-driven: This approach would suggest that “ You should sell what you can make” Accordingly, new products should be derived from production technology. This view is dominated by vigorous use of technology and simplicity of operations changes. Interfunctional view: New-product introduction is interfunctional in nature and requires cooperation among marketing, operations, engineering and other functions Using this approach the new- product design will fall some where between “making what you can sell” and “selling what you can make”. 5-9

10. 5-10 The top manager of miraculously successful Sony is saying; “ Our plan is to lead the public to new product rather than ask them what they want. The public does not know what is possible but we do.” No customer expressed a need for a Walkman sound system, but soon after Sony invented it, every one had to have music with them wherever they most. A similar example is air condition (Wills Carrier invened it and humanbeing had to use it wherever they want). All enterprises today must use quick-connect electronic interfaces to coordinate product creation resource chains (CAD). Chrysler reduced its product development cycle from over 60 months to 36 month or less in the late 1980 s. Nowaday this cycle is about 12 month in the automotıve industry. For example last year (2014) Audio will offer 13 new models automobile to the market.

11. M AJOR FUNCTIONS OF P RODUCT P LANNING Desingning for the customer; industrial design Reducing Time-to-Market;speed Improving Quality of Design;QFD Product Development:generating new product ideas Desing Process;linking desing and manufacturing, design for manufacturability, process selection Special Considerations in Service Design 5-11

12. F ORM AND F UNCTIONAL D ESIGN Copyright 2006 John Wiley & Sons, Inc. 5-12 Form Design how product will look? Functional Design reliability maintainability usability

13. R APID P ROTOTYPING Build a prototype form design functional design production design Test prototype Revise design Retest 5-13 Copyright 2006 John Wiley & Sons, Inc.

14. U SABILITY Ease of use of a product or service ease of learning ease of use ease of remembering how to use frequency and severity of errors user satisfaction with experience (Simplicity& Compexity&Technology) 5-14 Copyright 2006 John Wiley & Sons, Inc.

15. HTTP :// WWW. YOUTUBE. COM / WATCH ? V = O F JQ M2 B1 E REHTTP :// WWW. YOUTUBE. COM / WATCH ? V = O F JQ M2 B1 E RE SAP HTTP :// WWW. YOUTUBE. COM / WATCH ? V =WU GSY Y OT L K Q YOUR CAR HTTP :// WWW. YOUTUBE. COM / WATCH ? V =WU GSY Y OT L K Q http://www.youtube.com/watch?v=9pIW62ZEEhE http://www.youtube.com/watch?v=DN__D5ixme0 mobilephone http://www.youtube.com/watch?v=2IMoctL1C2g Mercedes-mehmettunga http://www.youtube.com/watch?v=F5vULbhGQu8 Bicycles http://www.youtube.com/watch?v=r2PzpiD-Sh0 Levitation http://www.youtube.com/watch?v=eVJtOO7mS3I Future phone 5-15 Copyright 2006 John Wiley & Sons, Inc.

16. A NALYTICAL HıERARCHY PROCESS 5-16 Copyright 2006 John Wiley & Sons, Inc.

17. S OME METHODS CAN HELP YOU ! 5-17 Copyright 2006 John Wiley & Sons, Inc.

18. 5-18 Copyright 2006 John Wiley & Sons, Inc.

19. 5-19 Copyright 2006 John Wiley & Sons, Inc.

20. 5-20 Copyright 2006 John Wiley & Sons, Inc.

21. A N EW CAR EXAMPLE ; 5-21 Copyright 2006 John Wiley & Sons, Inc.

22. T O USE AHP YOU NEED ; 5-22 Copyright 2006 John Wiley & Sons, Inc.

23. 5-23 Copyright 2006 John Wiley & Sons, Inc.

24. H ERE IS YOUR ANSWER ! 5-24 Copyright 2006 John Wiley & Sons, Inc.

25. 5-25 Copyright 2006 John Wiley & Sons, Inc.

26. P RODUCTION D ESIGN  Simplification reducing number of parts, assemblies, or options in a product  Standardization using commonly available and interchangeable parts  Modularity combining standardized building blocks, or modules, to create unique finished products 5-26 Copyright 2006 John Wiley & Sons, Inc.

27. 5-27 Copyright 2006 John Wiley & Sons, Inc. Design Simplification (b) Revised design One-piece base & elimination of fasteners (c) Final design Design for push-and-snap assembly (a) Original design Assembly using common fasteners

28. M EASURE D ESIGN Q UALITY Copyright 2006 John Wiley & Sons, Inc. 5-28 % of revenue from new products or services % of products capturing 50% or more of market % of process initiatives yielding a 50% or more improvement in effectiveness % of suppliers engaged in collaborative design % of parts that can be recycled % of parts used in multiple products % of parts with no engineering change orders Average number of components per product Things gone wrong (TGW)

29. Q UALITY F UNCTION D EPLOYMENT (QFD) Translates voice of customer into technical design requirements Displays requirements in matrix diagrams first matrix called “house of quality” series of connected houses 5-29 Copyright 2006 John Wiley & Sons, Inc.

30. " A GROUP OF COURAGEOUS PEOPLE WORKING IN HARMONY PURSUING THE FINEST DETAIL TO UNLOCK THE ORGANIZATION AND ROLL OUT PRODUCTS THAT THE MULTITUDES IN THE MARKETPLACE WILL VALUE." G LENN M AZUR 5-30 Copyright 2006 John Wiley & Sons, Inc.

31. V OICE OF THE C USTOMER THROUGH EACH STAGE OF THE PRODUCT DEVELOPMENT AND PRODUCTION PROCESS, THAT IS, THROUGH THE PRODUCT REALIZATION CYCLE. T HESE REQUIREMENTS ARE THE COLLECTION OF CUSTOMER NEEDS, INCLUDING ALL SATISFIERS, EXCITERS / DELIGHTERS, AND DISSATISFIERS. 5-31 Copyright 2006 John Wiley & Sons, Inc.

32. What Does QFD Do? Better Designs in Half the Time! QFD Is a Productivity Enhancer CUSTOMERCONCEPT PlanDesignRedesignManufacture Plan Design RedesignManufacture Benefits “Traditional Timeline”

33. A S ERIES OF C ONNECTED QFD H OUSES 5-33 Copyright 2006 John Wiley & Sons, Inc. Customer requirements House of quality Product characteristics A-1 Product characteristics Parts deployment Part characteristics A-2 Part characteristics Process planning Process characteristics A-3 Process characteristics Operating requirements Operations A-4

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35. H ISTORY OF QFD Dr. Mizuno, Prof. Emeritus Mitsubishi Heavy Industries Kobe Shipyards, 1972 Toyota Minivans (1977 Base) 1979 - 20% Reduction In Start-Up Costs 1982 - 38% 1984 - 61% Dr. Clausing, Xerox, 1984 Any Manufacturing Or Service Industry

36. Product Selection Product is the structuring of competent parts or activities so that as a unit they can provide a specified value. Product specification is typically an engineering function. In service industries requirement. Design, production an marketing costs are reduced by standardizing and simplifying the product. After prototype units one designed and produced, the products are further analyzed and tested to see how well the quality, performance and costs conform to the design objectives. Simplification may take place to reduce unnecessary variety in the product line by discussing the number and variety of product produced. Product selection are influenced by; 1.The firm’s resource and technology base 2.The market environment 3.The firm’s motivation to use capabilities to meet the need of the market place. 5-36 Copyright 2006 John Wiley & Sons, Inc.

37. Product-Mix Decision Within the product-line grouping, decision must be made to select which mix of products to in view of costs, capacity and other limitation. Linear programming is a useful technique for assisting in product-mix decisions. It applies to situations where there firm has a demand for whatever quantity of two or more products it can produce. Another typical application is for the selection of the least costly mix of raw materials. Linear Programming LP is a mathematical technique for maximizing or minimizing a linear objective function, subject to linear constraints. It has wide variety of applications. It assumes that cost and revenue values are known (certainty) profits from various activities are additive, resource quantity for various activities are additive (additivity) it doesn’t allow negative production values (non-negativity) It has widespread application such as mix product decision, capacity planning capital budgeting, line balancing, agregate planning and scheduling. 5-37

38. Objective (Goal) To maximize total profit Decision Variables What do we have to decide on? What are the variables that we can control ? We have to decide on amounts of products to be produced. 5-38 Copyright 2006 John Wiley & Sons, Inc.

39. 1-Graphical solution method: For the simple linear problems, the easiest procedure is the graphical method. Example1. A chemical firm produces automobile cleaner X and polisher Y and realizes $10 profit on each box of X and $30 on Y. Both products require processing through the same machines A and B, but X requires 4 hours in A 8 in B, where as Y requires 6 hours in A and 4 in B. During the forthcoming week machines A and B have 12 and 16 hours of available capacity, respectively Assuming that demands exists for both products, how many boxes of each should be produces to realize the optimal profit P? First step: Formulate the problem in ten of linear objective function and linear const. X: No.of cleaner X to be produced. Y: No. of polisher Y to be produced. Objective function is: Maximize P = $10 x + $30y The constraints are: 4x + 6y  12 8x + 4y  16 Alsox and y  0 in two dimensions. We begin by constructing a graph that represents the LP 5-39.

40. Second step: Variables are X and Y. The constraint. Are plotted as equalities. We use a ruler to make a heavy horizontal line for the X axis and a heavy vertical line for the Y axis. To graph: A: if x=0y=2 if y=0x=3 B:ifx=0y=4 ify=0x=2 Note that the graph established a feasible region bounded by the explicit capacity const of A and B and the implicit constraints that production of x>0 and production y>0 5-40

41. Third step: The slope of the objective function. P =10x+30y The standard slop intercept form of a linear equation is Y= mX + b where m is the slope of the line 8that is, change in Y pen unit change in x) and b is there Y intercept. Expressing our objectives in this form, we have. 30 y = -10x +P Y= (-1/3) x + P/30 The slope = -1/3; that is, the line decreases one unit in Y for every three positive units of X. This is plotted at any convenient spot within the feasible solution region. We could plot a similar line for any other value of Z. These profit lines are parallel. Fourth step: The slope of the objective function is moved away from the origin until restrained by the furthermost intersection of A and the implicit constraint x>0. The optimal solution will always be at a corner in the feasible region. This corner will be the last point in the feasible solution region 5-41

42. Fifth step: The arrow point to the solution, within is determined by the x and y coordinates at time co. In this example x=0 y=2 P = $10 (0) + $30(2) = $60 4(0)+6(2)  1212=12 8(0)+4(2)  l68  16 In this example the firm should produce no cleaner and two boxes of polisher for a profit $60. We can see from the graph, the constraint imposed by machine B (8x+4y <16) has no effect, for it is the 12 hours of machine A (4x+6y<12) that are constraining production of the more profitable polisher. The graph also reveals that profit would continue to increase if more hours could be made available on machine A up to the point of doubling output (to x=0 end y=4) At this point, the time available from machine B would become constraining 5-42

43. Ch 11 Supp - 4 © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e L INEAR P ROGRAMMING :E XAMPLE 2 M ODEL F ORMULATION Resource requirements Labor ClayRevenue Product(hr/unit)(lb/unit)($/unit) Bowl1440 Mug2350 There are 40 hours of labor and 120 pounds of clay available each day Decision variables x 1 = number of bowls to produce x 2 = number of mugs to produce

44. Ch 11 Supp - 5 © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e O BJECTIVE F UNCTION & C ONSTRAINTS Maximize Z = $40 x 1 + 50 x 2 Subject to x 1 + 2 x 2  40 hr (labor constraint) 4 x 1 + 3 x 2  120 lb (clay constraint) x 1, x 2  0 Solution is x 1 = 24 bowls x 2 = 8 mugs Revenue = $1,360

45. Ch 11 Supp - 6 © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e G RAPHICAL S OLUTION M ETHOD 1. Plot model constraint on a set of coordinates in a plane 2. Identify the feasible solution space on the graph where all constraints are satisfied simultaneously 3. Plot objective function to find the point on boundary of this space that maximizes (or minimizes) value of objective function

46. Ch 11 Supp - 7 © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e G RAPH O F P OTTERY P ROBLEM 203040506010 20 30 40 50 60 10 x1x1 x2x2 4 x 1 + 3 x 2  120 lb x 1 + 2 x 2  40 hr Area common to both constraints

47. Ch 11 Supp - 8 © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e P LOT O BJECTIVE F UNCTION $800 = 40x 1 + 50 x 2 Optimal point 20304010 x1x1 20 30 40 10 x2x2 B.

48. Ch 11 Supp - 9 © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e C OMPUTING O PTIMAL V ALUES A. x 1 + 2 x 2 =  40 4 x 1 + 3 x 2 =  120 4 x 1 + 8 x 2 =  160 -4 x 1 - 3 x 2 =  120 5 x 2 = 40 x 2 = 8 x 1 + 2 (8) =  40 x 1 =  24 Z = $50(24) + $50(8) Z = $1,360 8 B C x 1 + 2 x 2 =  40 4 x 1 + 3 x 2 =  120 20304010 x1x1 20 30 40 10 x2x2

49. Ch 11 Supp - 10 © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e E XTREME C ORNER P OINTS A. B C x 1 = 0 bowls x 2 =  20 mugs Z = $1,000 x 1 = 224 bowls x 2 =  8 mugs Z = $1,360 x 1 = 30 bowls x 2 =  0 mugs Z = $1,200 20304010 x1x1 20 30 40 10 x2x2

50. Ch 11 Supp - 11 © 2000 by Prentice-Hall Inc Russell/Taylor Oper Mgt 3/e O BJECTIVE F UNCTION D ETERMINES O PTIMAL S OLUTION A B C Optimal point: x 1 = 30 bowls x 2 =  0 mugs Z = $2,100 20304010 x1x1 20 30 40 10 x2x2 4 x 1 + 3 x 2  120 lb x 1 + 2 x 2  40 hr Z = 70 x 1 + 20 x 2

51. G RAPHıCAL SOLUTıON METHOD EXAMPLE 3: A company is already producing some products. However there are some idle capacities of the facilities. There are three plants. The idle capacities in terms of labor hours per week are as follows The management wants to utilize the unused capacities by producing two new products. Product-1: An 8 foot glass door with aliminum framing Product-2: A 4x6 double hung window with wood- framing 5-51 Copyright 2006 John Wiley & Sons, Inc. Plant Idle Capacity(hours/week) Plant -1 4 Plant -2 12 Plant -3 18

52. The products are produced in batches Plant-1 produces aliminum frames Plant-2 produces wood frames Plant-3 produces glass and assembles the products The unit profits per products are 3000 and 5000 respectively. The labor hours required to produce different parts of the products at different plants are as follows : 5-52 Copyright 2006 John Wiley & Sons, Inc. Plant Production Time per Batch (hours) Product -1 Product-2 Plant -1 10 Plant-202 Plant-332

53. 5-53 Copyright 2006 John Wiley & Sons, Inc.Constraints Resources are limited 4 hours available at Plant -1 12 hours available at Plant -2 18 hours available at Plant-3 Objective Function Total profit to be maximized

54. x1 x2 G RAPHICAL S OLUTION

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62. E XAMPLE :4 The Primo Insurance Company is introducing two new product lines: special risk insurance and mortgages. The expected profit is $5 per unit on special risk insurance and $2 per unit on mortgages. Management wishes to establish sales quotas for the new product lines to maximize total expected profit. The work requirements are as follows: (a) Formulate a linear programming model for this problem. (b) Use the graphical method to solve this model. 5-62 Copyright 2006 John Wiley & Sons, Inc.

63. X1= no. of special risk insurance X2= no. of mortgage. Z Max = 5X 1 +2X 2 s.t. 3X1+2X2<=2400 X2<=800 2X1<=1200 X1,X2>=0 5-63 Copyright 2006 John Wiley & Sons, Inc.

64. 5-64 Copyright 2006 John Wiley & Sons, Inc.