Page 120 - Design for Six Sigma a Roadmap for Product Development
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Product Development Process and Design for Six Sigma  95


           ■ Taguchi method, parameter design, tolerance design
           ■ Reliability-based design
           ■ Robustness assessment

           3.7.4 Phase 4: Validate the design (V)
           After the parameter and tolerance design is completed, we will move
           to the final verification and validation activities.
           Step 1: Pilot test and refining. No product or service should go directly
           to market without first piloting and refining. Here we can use design
           failure mode–effect analysis (DFMEA) as well as pilot and small-scale
           implementations to test and evaluate real-life performance.

           Step 2: Validation and process control. In this step we will validate the
           new entity to make sure that the end result (product or service) as
           designed meets the design requirements and that the process controls
           in manufacturing and production are established in order to ensure
           that critical characteristics are always produced to specification of the
           optimization (O) phase.

           Step 3: Full commercial rollout and handover to new process owner. As
           the design entity is validated and process control is established, we
           will launch full-scale commercial rollout and the new entity, together
           with the supporting processes, can be handed over to design and
           process owners, complete with requirements settings and control and
           monitoring systems.
             The following DFSS tools are used in this phase:

           ■ Process capability modeling
           ■ DOE
           ■ Reliability testing
           ■ Poka-yoke, errorproofing
           ■ Confidence analysis
           ■ Process control plan
           ■ Training

           3.8 More on Design Process
           and Design Vulnerabilities

           An efficient DFSS application can be achieved when analytical tools
           are combined with science-based design tools such as axiomatic design
           (Suh 1990), where modeling of the  “design structure” carries great
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