The rapid growth of the electronics industry has spurred dramatic changes in electronic parts. Increases in speed, reductions in feature size and supply voltage, and changes in interconnection and packaging technologies are becoming events that occur almost monthly. Consequently, many of the electronic parts that compose a product have life cycles that are significantly shorter than the life cycle of the product. This life cycle mismatch problem requires that during design, engineers be cognizant of which parts will be available and which parts may be obsolete during a product’s life. This problem is especially prevalent in avionics and military systems, where systems may encounter obsolescence problems before being fielded and nearly always experience obsolescence problems during their field life. This problem is exacerbated by manufacturing that takes place over long periods of time, and the high cost of system re-qualification that makes the design refreshes extremely expensive.
Many part obsolescence mitigation strategies exist including: life time buy, last-time buy, part replacement, aftermarket source, uprating, emulation, re-engineering, salvage, and ultimately redesign of the system. Design refresh (or redesign) has the advantage of treating multiple existing and anticipated obsolescence problems concurrently and additionally allows for functional upgrades. Unfortunately, design refresh is also often a very expensive option, not just in non-recurring engineering costs, but also in potential system re-qualification costs.
The MOCA Analysis
A methodology and it’s implementation has been developed for determining the part obsolescence impact on life cycle sustainment costs for the long field life electronic systems based on future production projections, maintenance requirements and part obsolescence forecasts (Figure 1). Based on a detailed cost analysis model, the methodology determines the optimum design refresh plan during the field-support-life of the product. The design refresh plan consists of the number of design refresh activities, their respective calendar dates and content to minimize the life cycle sustainment cost of the product. The methodology supports user determined short- and long-term obsolescence mitigation approaches on a per part basis, variable look-ahead times associated with design refreshes, and allows for inputs to be specified as probability distributions that can vary with time.
Additional details of the model formulations and examples produced using the model can be found in the following publications:
R. Nelson III and P. Sandborn, “Strategic Management of Component Obsolescence Using Constraint-Driven Design Refresh Planning,” ASME International Design Engineering Conferences & Computers and Information in Engineering Conference, Washington DC, August 2011.
P. Sandborn, "Strategic Management of DMSMS in Systems," DSP Journal, pp. 24-30, April/June 2008.
J. Myers and P. Sandborn, "Integration of Technology Roadmapping Information and Business Case Development into DMSMS-Driven Design Refresh Planning of the V-22 Advanced Mission Computer,"Proceedings of the 2007 Aging Aircraft Conference, Palm Springs, CA, April 2007.
P. Singh and P. Sandborn, "Obsolescence Driven Design Refresh Planning for Sustainment-Dominated Systems," The Engineering Economist, Vol. 51, No. 2, pp. 115-139, April-June 2006.
P. Singh and P. Sandborn, “Forecasting Technology Insertion Concurrent with Design Refresh Planning for COTS-Based Electronic Systems,” Proc. Reliability and Maintainability Symposium, Arlington, VA, Jan. 2005.
P. Sandborn, "Beyond Reactive Thinking – We Should be Developing Pro-Active Approaches to Obsolescence Management Too!," DMSMS Center of Excellence Newsletter, Vol. 2, Issue 3, pp. 4, 9, July 2004.
P. Singh, P. Sandborn, T. Geiser, and D. Lorenson, "Electronic Part Obsolescence Driven Design Refresh Planning," International Journal of Agile Manufacturing, Vol. 7, No. 1, pp. 23-32, 2004.
P. Singh, P. Sandborn, T. Geiser, and D. Lorenson, "Electronic Part Obsolescence Driven Design Refresh Optimization," Proc. International Conference on Concurrent Engineering, pp. 961-970, Cranfield University, UK, July 2002.
P. Singh, P. Sandborn, D. Lorenson, and T. Geiser, "Determining Optimum Redesign Plans for Avionics Considering Electronic Part Obsolescence Forecasts," in Proc. World Aviation Congress, Phoenix, AZ, November 2002. (SAE Technical Paper: 2002-1-3012)
P. Sandborn and P. Singh, "Electronic Part Obsolescence Driven Design Refresh Optimization," in Proc. FAA/DoD/NASA Aging Aircraft Conference, San Francisco, CA, September 2002.
P. Sandborn, P. Singh, T. Herald, and J. Houston, "Optimum Technology Insertion into Systems Based on the Assessment of Viability," IEEE Trans. on Components and Packaging Technologies, Vol. 26, No. 4, 2003.
For more information, please contact Prof. Peter Sandborn