Product Development Product Selection and Development Stages Figure

Product Development

Product Selection and Development Stages • Figure 5. 4, pg. 138

Quality Function Deployment (DFD) • 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 technique for defining the relationship between customer desires and the developed product (or service) (Discuss Example 1: pgs 139 -140)

Deploying the Quality Effort • Discuss Figure 5. 5 • The final outcome: Product Excellence, i. e. , determining what the customer wants and providing it!

Organizing the Product Development Effort • The traditional US approach (department-based): Research & Development => Engineering => Manufacturing => 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

Manufacturability and Value Engineering • Promote improved designs and product specifications through the R&D, design and production stages of the product development, by seeking to – Control the product complexity – (further) standardize the employed components – Improve job design and job safety – Improve the product maintainability / serviceability – promote robust design practices

Some current issues in product design • Robustness: the insensitivity of the product performance to small variations in the production or assembly process => ability to support product quality more reliably and costeffectively. • Modularity: the structuring of the end product through easily segmented components that can also be easily interchanged or replaced => ability to support flexible production and product customization; increased product serviceability. • Environmental friendliness: – Safe and environmentally sound products – Minimizing waste of raw materials and energy – Reducing environmental liabilities – Increasing cost-effectiveness of complying with environmental regulations – Being recognized as good corporate citizen. – (example: BMW-Figure of pg. 145)

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 => more money is funneled to the product development and the relative risks become higher. • Product development strategies for time-based competition (Figure 5. 7, pg. 147)

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 product’s planned and changing components are accurately identified and for which control of accountability of change are maintained

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

“Make-or-buy” decisions • Deciding whether to produce a product component “inhouse”, 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

A simple economic trade-off model for the “Make or Buy” problem Model parameters: • c 1 ($/unit): cost per unit when item is outsourced (item price, ordering and receiving costs) • C ($): required capital investment in order to support internal production • c 2 ($/unit): variable production cost for internal production (materials, labor, variable overhead charges) • Assume that c 2 < c 1 • X: total quantity of the item to be outsourced or produced internally Total cost as a function of X c 1*X C+c 2*X C X 0 = C / (c 1 -c 2) X

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 X 0 = (12, 500+1, 000)/(1. 55 -1. 12) = 31, 395 > 20, 000 Buy!

Evaluating Alternatives in Product Design 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 3)

The Silicon Inc. Example • Developing and marketing a new microprocessor • Company Options: – Purchase a sophisticated CAD system: $500, 000 => manufacturing cost: $40/unit – Hiring and training three new engineers: $375, 000 => manufacturing cost $50/unit – do nothing! • Possible market responses: – Favorable: 25, 000 units sold at $100 each – 40% chances – Unfavorable: 8000 units sold at $100 each – 60% chances • Pick an option that maximizes the expected monetary value (EMV)