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Preventive Problem Solving2018-04-26T09:58:14+00:00

Preventive Problem Solving – Resilient Design and Development

In an increasingly complex and customer-centric environment, new product design and development must go beyond product function and characteristics. To deliver reliable, trouble-free products, provisions must be made for manufacturing variation and the effects of operating and environmental energies. Early discovery of potential system weakness is essential to achieve a trouble-free launch.


Shainin identifies and mitigates areas of risk relative to performance expectations, life cycle requirements and manufacturing variations. By combining Shainin`s powerful reactive problem solving experience and proactive problem prevention strategies, Shainin is able to achieve superior product performance and reliability for clients. Shainin`s ability to verify design and manufacturing risks with simple targeted simulations or tests supports timely product and process modifications to ensure a trouble-free launch.


Shainin`s work results in a robust design solution that avoids: last minute design changes, product launch delays and post start of production (SOP) modifications. Throughout the product life cycle, Shainin solutions contribute to improved product performance, lower warranty costs and improved manufacturing efficiency.

Shainin Design Risk Mitigation identifies the high risk functions of a new product at concept development. A complex system or subsystem is transformed into a set of simple, straight forward simulations or tests that quickly provide insight on performance and reliability. The insights revealed allow designers to minimize risks while the design is still fluid.

Design Risk Mitigation starts with identifying and prioritizing high risk functions through a focused risk priority number Pareto. Once the highest risk functions are identified, system functions are mapped and the design is functionally decomposed using Function Model software. The critical inputs identified from the Function Model are then mapped to the high risk functions on a Linkage Matrix. Next measurement systems are developed and verified for use in conceptualized failure mode simulation and testing. Design failure modes and potential failure modes are identified and the physics behind product behavior is understood enabling changes to reduce risk early in concept development.

Shainin Manufacturing Risk Mitigation identifies high risk manufacturing operations for new or modified products. Manufacturing Risk Mitigation reveals and controls the critical manufacturing parameters that impact product performance and reliability.

Manufacturing Risk Mitigation starts with identifying and prioritizing high risk manufacturing processes through a focused risk priority number Pareto. Once the highest risk processes are identified, the process operations and steps are analyzed and decomposed. Next the high risk processes are characterized to understand all manufacturing parameters that contribute to product variation. Manufacturing failure modes and potential failure modes are identified and understood. Process changes to reduce manufacturing risk are implemented early in production preparation and effective control plans are developed.

Shainin Warranty Risk Mitigation reveals a design’s weakest link(s) in the most time efficient and economical fashion possible. The key deliverable of Warranty Risk Mitigation is a sample of units tested to failure based on the customer’s usage profile and environments with statistical estimates for when each weak link will fail.

Warranty Risk Mitigation starts with understanding the system and environmental energies. The energy whose foolish failure mode is closest to the normal operating range is identified to determine the limiting factor in overstress testing to avoid creating unrealistic failure modes. The reliability test plan is then developed by defining the normal operating rectangle and overstress probe steps. Next the reliability test plan is executed by testing a small sample size of product to failure. The results are analyzed and interpreted to understand the product’s weakest failure mode(s) and predict with statistical confidence when the product will fail prior to launch. Lastly, service monitoring is implemented to determine if there are any customer use profiles or environments not previously incorporated into the reliability test plan that could lead to premature failure.

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