Managing obsolescence of embedded hardware and software in secure and trusted systems

Abstract

Obsolescence of integrated systems which contain hardware and software is a problem that affects multiple industries and can occur for many reasons, including technological, economic, organizational, and social factors. It is especially acute in products and systems that have long life cycles, where a high rate of technological innovation of the subcomponents result in a mismatch in life cycles between the components and the systems. While several approaches for obsolescence forecasting exist, they often require data that may not be available. This paper describes an approach using non-probabilistic scenarios coupled with decision analysis to investigate how particular scenarios influence priority setting for products and systems. Scenarios are generated from a list of emergent and future conditions related to obsolescence. The key result is an identification of the most and least disruptive scenarios to the decision maker’s priorities. An example is presented related to the selection of technologies for energy islanding, which demonstrates the methodology using six obsolescence scenarios. The paper should be of broad interest to scholars and practitioners engaged with enterprise risk management and similar challenges of large-scale systems.

Keywords

enterprise risk management / diminishing manufacturing sources and material shortages / scenario-based preferences / systems engineering / deep uncertainty / product life cycle

References

[1] Abdi H (2007). The Kendall rank correlation coefficient. In: Salkind N, ed. Encyclopedia of Measurement and Statistics. Thousand Oaks: Sage

[2] Belton V, Stewart T J (2002). Multiple Criteria Decision Analysis: An Integrated Approach. Boston: Kluwer Academic Publishers

[3] Bromberger J, Kelly R (2017). Additive manufacturing: a long-term game changer for manufacturers. New York: McKinsey & Company

[4] Collier Z A, Hendrickson D, Polmateer T L, Lambert J H (2018). Scenario analysis and PERT/CPM applied to strategic investment at an automated container port. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 4(3): 04018026

[5] Collier Z A, Lambert J H (2018). Time management of infrastructure recovery schedules by anticipation and valuation of disruptions. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 4(2): 04018012

[6] Collier Z A, Lambert J H (2019). Evaluating management actions to mitigate disruptive scenario impacts in an e-commerce system integration project. IEEE Systems Journal, 13(1): 593–602

[7] Collier Z A, Walters S, DiMase D, Keisler J M, Linkov I (2014). A semi-quantitative risk assessment standard for counterfeit electronics detection. SAE International Journal of Aerospace, 7(1): 171–181

[8] Connelly E B, Colosi L M, Clarens A F, Lambert J H (2015). Risk analysis of biofuels industry for aviation with scenario-based expert elicitation. Systems Engineering, 18(2): 178–191

[9] Davis J, Sullivan J (2017). Supply chain risk—what is it? Defense AT&L, 46(2): 15–18

[10] de Grip A (2006). Evaluating human capital obsolesce. In: Proceedings of the Joint EC-OECD Seminar on Human Capital and Labour Market Performance, Brussels, Belgium

[11] de Siqueira Santos S, Takahashi D Y, Nakata A, Fujita A (2014). A comparative study of statistical methods used to identify dependencies between gene expression signals. Briefings in Bioinformatics, 15(6): 906–918

[12] DiMase D, Collier Z A, Carlson J, Gray R B Jr, Linkov I (2016). Traceability and risk analysis strategies for addressing counterfeit electronics in supply chains for complex systems. Risk Analysis, 36(10): 1834–1843

[13] DoD (2015a). Defense Acquisition University Glossary. 16th ed. Fort Belvoir: Defense Acquisition University Press

[14] DoD (2015b). Diminishing Manufacturing Sources and Material Shortages: Cost Metrics. Fort Belvoir: Defense Standardization Program Office

[15] DoD (2016). SD-22—Diminishing Manufacturing Sources and Material Shortages (DMSMS): a Guidebook of Best Practices for Implementing a Robust DMSMS Management Program. Fort Belvoir: Defense Standardization Program Office

[16] Hamilton M C, Lambert J H, Connelly E B, Barker K (2016). Resilience analytics with disruption of preferences and lifecycle cost analysis for energy microgrids. Reliability Engineering & System Safety, 150: 11–21

[17] Hamilton M C, Lambert J H, Valverde L J (2015). Climate and related uncertainties influencing research and development priorities. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 1(2): 04015005

[18] Hirsch A, Parag Y, Guerrero J (2018). Microgrids: a review of technologies, key drivers, and outstanding issues. Renewable & Sustainable Energy Reviews, 90: 402–411

[19] Kaplan S, Garrick B J (1981). On the quantitative definition of risk. Risk Analysis, 1(1): 11–27

[20] Karvetski C W, Lambert J H (2012). Evaluating deep uncertainties in strategic priority-setting with an application to facility energy investments. Systems Engineering, 15(4): 483–493

[21] Karvetski C W, Lambert J H, Keisler J M, Linkov I (2011a). Integration of decision analysis and scenario planning for coastal engineering and climate change. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 41(1): 63–73

[22] Karvetski C W, Lambert J H, Linkov I (2009). Emergent conditions and multiple criteria analysis in infrastructure prioritization for developing countries. Journal of Multi-Criteria Decision Analysis, 16(5‒6): 125–137

[23] Karvetski C W, Lambert J H, Linkov I (2011b). Scenario and multiple criteria decision analysis for energy and environmental security of military and industrial installations. Integrated Environmental Assessment and Management, 7(2): 228–236

[24] Kendall M (1938). A new measure of rank correlation. Biometrika, 30(1‒2): 81–93

[25] Lambert J H, Karvetski C W, Spencer D K, Sotirin B J, Liberi D M, Zaghloul H H, Koogler J B, Hunter S L, Goran W D, Ditmer R D, Linkov I (2012). Prioritizing infrastructure investments in Afghanistan with multiagency stakeholders and deep uncertainty of emergent conditions. Journal of Infrastructure Systems, 18(2): 155–166

[26] Lambert J H, Wu Y J, You H, Clarens A, Smith B (2013). Climate change influence on priority setting for transportation infrastructure assets. Journal of Infrastructure Systems, 19(1): 36–46

[27] Morgan M G (2014). Use (and abuse) of expert elicitation in support of decision making for public policy. Proceedings of the National Academy of Sciences of the United States of America, 111(20): 7176–7184

[28] Porter G Z (1998). An Economic Method for Evaluating Electronic Component Obsolescence Solutions. Boeing Company White Paper

[29] Reilly R F (2013). Consideration of functional and economic obsolescence in the assessment of industrial or commercial property. Journal of Property Tax Assessment & Administration, 10(1): 45–58

[30] Romero Rojo F J, Roy R, Kelly S (2012). Obsolescence risk assessment process best practice. Journal of Physics: Conference Series, 364: 012095

[31] Romero F J Rojo R, Roy E, Shehab (2010). Obsolescence management for long-life contracts: state of the art and future trends. International Journal of Advanced Manufacturing Technology, 49(9‒12): 1235–1250

[32] Sandborn P (2007). Software obsolescence—complicating the part and technology obsolescence management problem. IEEE Transactions on Components and Packaging Technologies, 30(4): 886–888

[33] Sandborn P (2013). Design for obsolescence risk management. Procedia CIRP, 11: 15–22

[34] Sandborn P, Prabhakar V, Ahmad O (2011). Forecasting electronic part procurement lifetimes to enable the management of DMSMS obsolescence. Microelectronics and Reliability, 51(2): 392–399

[35] Singh P, Sandborn P (2006). Obsolescence driven design refresh planning for sustainment-dominated systems. Engineering Economist, 51(2): 115–139

[36] Solomon R, Sandborn P A, Pecht M G (2000). Electronic part life cycle concepts and obsolescence forecasting. IEEE Transactions on Components and Packaging Technologies, 23(4): 707–717

[37] Song J S, Zipkin P H (1996). Managing inventory with the prospect of obsolescence. Operations Research, 44(1): 215–222

[38] Wnuk K, Gorschek T, Zahda S (2013). Obsolete software requirements. Information and Software Technology, 55(6): 921–940

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