Product and Process Design, Sourcing, Equipment Selection and Capacity Planning

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Product and Process Design,Sourcing, Equipment
Selection and Capacity Planning
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Major Topics

• Product and Process Design
• Documenting Product and Process Design
• Sourcing Decisions
• A simple Make or Buy model
• Decision Trees A scenario-based approach
• Equipment Selection and Capacity Planning

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Product Selection and Development
Stages(borrowed from Heizer Render)
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Quality Function Deployment (DFD) and the House
of Quality

• QFD The process of
• Determining what are the customer requirements
  / wants, and
• Translating those desires into the target product
  design.
• House of quality A graphic, yet systematic
  technique for defining the relationship between
  customer desires and the developed product (or
  service)

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House of Quality Example(borrowed from Heizer
Render)
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The House of Quality Chain(borrowed from
Heizer Render)
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Concurrent Engineering The current approach for
organizing the product and process development

• The traditional US approach (department-based)
• Research Development gt Engineering gt
  Manufacturing gt
• Production
• Clear-cut responsibilities but lack of
  communication and forward thinking!
• The currently prevailing approach
  (cross-functional team-based)
• Product development (or design for
  manufacturability, or value engineering) teams
  Include representatives from
• Marketing
• Manufacturing
• Purchasing
• Quality assurance
• Field service
• (even from) vendors
• Concurrent engineering Less costly and more
  expedient product development

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The time factor Time-based competition

• Some advantages of getting first a new product to
  the market
• Setting the standard (higher market control)
• Larger market share
• Higher prices and profit margins
• Currently, product life cycles get shorter and
  product technological sophistication increases gt
  more money is funneled to the product development
  and the relative risks become higher.
• The pressures resulting from time-based
  competition have led to higher levels of
  integrations through strategic partnerships, but
  also through mergers and acquisitions.

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Additional concerns in contemporary product and
process design

• promote robust design practices
• Robustness the insensitivity of the product
  performance to small variations in the production
  or assembly process gt ability to support product
  quality more reliably and cost-effectively.
• Control the product complexity
• Improve the product maintainability /
  serviceability
• (further) standardize the employed components
• Modularity the structuring of the end product
  through easily segmented components that can
  also be easily interchanged or replaced gt
  ability to support flexible production and
  product customizationincreased product
  serviceability.
• Improve job design and job safety
• Environmental friendliness safe and
  environmentally sound products, minimizing waste
  of raw materials and energy, complying with
  environmental regulations, ability for reuse,
  being recognized as good corporate citizen.

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Documenting Product Designs

• Engineering Drawing a drawing that shows the
  dimensions, tolerances, materials and finishes of
  a component. (Fig. 5.9)
• Bill of Material (BOM) A listing of the
  components, their description and the quantity of
  each required to make a unit of a given product.
  (Fig. 5.10)
• Assembly drawing An exploded view of the
  product, usually via a three-dimensional or
  isometric drawing. (Fig. 5.12)
• Assembly chart A graphic means of identifying
  how components flow into subassemblies and
  ultimately into the final product. (Fig. 5.12)
• Route sheet A listing of the operations
  necessary to produce the component with the
  material specified in the bill of materials.
• Engineering change notice (ECN) a correction or
  modification of an engineering drawing or BOM.
• Configuration Management A system by which a
  products planned and changing components are
  accurately identified and for which control of
  accountability of change are maintained

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Documenting Product Designs (cont.)

• Work order An instruction to make a given
  quantity (known as production lot or batch) of a
  particular item, usually to a given schedule.
• Group technology A product and component coding
  system that specifies the type of processing and
  the involved parameters, allowing thus the
  identification of processing similarities and the
  systematic grouping/classification of similar
  products. Some efficiencies associated with group
  technology are
• Improved design (since the focus can be placed on
  a few critical components
• Reduced raw material and purchases
• Improved layout, routing and machine loading
• Reduced tooling setup time, work-in-process and
  production time
• Simplified production planning and control

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Engineering Drawing Example(borrowed from Heizer
Render)
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Bill of Material (BOM) Example(borrowed from
Heizer Render)
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Assembly Drawing Chart Examples(borrowed from
Heizer Render)
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Operation Process Chart Example(borrowed from
Francis et. al.)
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Route Sheet Example(borrowed from Francis et.
al.)
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Make-or-buy decisions

• Deciding whether to produce a product component
  in-house, or purchase/procure it from an
  outside source.
• Issues to be considered while making this
  decision
• Quality of the externally procured part
• Reliability of the supplier in terms of both item
  quality and delivery times
• Criticality of the considered component for the
  performance/quality of the entire product
• Potential for development of new core
  competencies of strategic significance to the
  company
• Existing patents on this item
• Costs of deploying and operating the necessary
  infrastructure

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A simple economic trade-off model for the Make
or Buy problem

• Model parameters
• c1 (/unit) cost per unit when item is
  outsourced (item price, ordering and receiving
  costs)
• C () required capital investment in order to
  support internal production
• c2 (/unit) variable production cost for
  internal production (materials, labor,variable
  overhead charges)
• Assume that c2 lt c1
• X total quantity of the item to be outsourced
  or produced internally

c1X
Total cost as a function of X
Cc2X
C
X
X0 C / (c1-c2)
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Example Introducing a new (stabilizing) bracket
for an existing product

• Machine capacity available
• Required infrastructure for in-house production
• new tooling 12,500
• Hiring and training an additional worker 1,000
• Internal variable production (raw material
  labor) cost 1.12 / unit
• Vendor-quoted price 1.55 / unit
• Forecasted demand 10,000 units/year for next 2
  years
• ?
• X0 (12,5001,000)/(1.55-1.12) 31,395 gt
  20,000
• ?
• Buy!

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Evaluating Alternatives through Decision Trees

• Decision Trees A mechanism for systematically
  pricing all options / alternatives under
  consideration, while taking into account various
  uncertainties underlying the considered
  operational context.
• Example
• An engineering consulting company (ECC) has been
  offered the design of a new product.The price
  offered by the customer is 60,000.
• If the design is done in-house, some new software
  must be purchased at the price of 20,000, and
  two new engineers must be trained for this effort
  at the cost of 15,000 per engineer.
• Alternatively, this task can be outsourced to an
  engineering service provider (ESP) for the cost
  of 40,000. However, there is a 20 chance that
  this ESP will fail to meet the due date requested
  by the customer, in which case, the ECC will
  experience a penalty of 15,000. The ESP offers
  also the possibility of sharing the above penalty
  at an extra cost of 5,000 for the ECC.
• Find the option that maximizes the expected
  profit for the ECC.

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Decision Trees Example
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Technology selection

• The selected technology must be able to support
  the quality standards set by the corporate /
  manufacturing strategy
• This decision must take into consideration future
  expansion plans of the company in terms of
• production capacity (i.e., support volume
  flexibility)
• product portfolio (i.e., support product
  flexibility)
• It must also consider the overall technological
  trends in the industry, as well as additional
  issues (e.g., environmental and other legal
  concerns, operational safety etc.) that might
  affect the viability of certain choices
• For the candidates satisfying the above concerns,
  the final objective is the minimization of the
  total (i.e., deployment plus operational) cost

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Production Capacity

• Design capacity the theoretical maximum output
  of a system, typically stated as a rate, i.e.,
  product units / unit time.
• Effective capacity The percentage of the design
  capacity that the system can actually achieve
  under the given operational constraints, e.g.,
  running product mix, quality requirements,
  employee availability, scheduling methods, etc.
• Plant utilization actual prod. rate / design
  capacity
• Plant efficiency actual prod. rate / (effective
  capacity x
• design capacity)
• Notice that
• actual prod. rate (design capacity) x
  (utilization)
• (design capacity) x (effective capacity) x
  (efficiency)

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Capacity Planning

• Capacity planning seeks to determine
• the number of units of the selected technology
  that needs to be deployed in order to match the
  plant (effective) capacity with the forecasted
  demand, and if necessary,
• a capacity expansion plan that will indicate the
  time-phased deployment of additional modules /
  units, in order to support a growing product
  demand, or more general expansion plans of the
  company (e.g., undertaking the production of a
  new product in the considered product family).
• Frequently, technology selection and capacity
  planning are addressed simultaneously, since the
  required capacity affects the economic viability
  of a certain technological option, while the
  operational characteristics of a given technology
  define the production rate per unit deployed and
  aspects like the possibility of modular
  deployment.

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Quantitative Approaches to Technology Selection
and Capacity Planning

• All these approaches try to select a technology
  (mix) and determine the capacity to be deployed
  in a way that it maximizes the expected profit
  over the entire life-span of the considered
  product (family).
• Expected profit is defined as expected revenues
  minus deployment and operational costs.
• Typically, the above calculations are based on
  net present values (NPVs) of the expected costs
  and revenues, which take into consideration the
  cost of money NPV (Expense or Revenue) /
  (1i)N
• where i is the applying interest rate and N the
  time period of the considered expense.
• Possible methods used include
• Break-even analysis, similar to that applied to
  the make or buy problem, that seeks to
  minimizes the total (fixed variable) cost.
• Decision trees which allow the modeling of
  problem uncertainties like uncertain market
  behavior, etc., and can determine a strategy as a
  reaction to these unknown factors.
• Mathematical Programming formulations which allow
  the optimized selection of technology mixes.

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Technology Selection and Capacity Planning
through Mathematical Programming (MP)

• Model Parameters
• i ? 1,,m technology options
• j?? 1,,n product (families) to be supported
  in the considered plant
• D_j forecasted demand per period for product j
  over the considered planning horizon
• C_i fixed production cost per period for one
  unit of technology option i
• v_ij variable production cost for of using one
  unit of technology i for one (full) period
  to produce (just) product j
• a_ij number of units of product j that can be
  produced in one period by one unit of
  technology option i.
• Model DecisionVariables
• y_i number of units of technology i to be
  deployed (nonnegative integer)
• x_ij production capacity of technology i used at
  each period to produce product j
  (nonnegative real, i.e., it can be fractional)

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The MP formulation
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Reading Assignment

• Chapter 1 Section 1.11 and Appendix 1-A.
• Also you are encouraged to read Chapter
  1Section1.10.