Selection of obsolescence resolution strategy based on a multi criteria decision model

A component becomes obsolete when it is no longer available from its original manufacturer in its original form. Component obsolescence is a significant problem in the electronics industry. There are different strategies employed to address this problem, for example, using an alternative part, life time buy, redesign etc. Often, techniques used in industry select one of these options based on the most economical solution as determined by minimizing direct costs. However, there are factors other than cost, such as the number of suppliers, time constraints, reliability of the solution etc., which may play a crucial role in determining an overall best decision. In addition, there are multiple stakeholders like design, operations, manufacturing, sales, service etc., who might have different opinions when it comes to obsolescence management. This research provides a multi criteria decision model that will consider the trade-offs among multiple factors and provide the decision maker solution that will be acceptable to a wide variety of stakeholders as well as being viable from the company\u27s perspective. The model is based on multi attribute utility theory. It will provide the stakeholders a platform to express their preferences and experience in the decision process. And, based on the overall utility value, the most suitable obsolescence resolution strategy for a specific application will be provided. The research provides a hypothetical case study in order to illustrate the application and usage of the model

The role of BIM in tackling obsolescence, climate change, and sustainability

Although the BIM technology is applicable to both new and existing buildings, it is arguably more established in the former than the latter. This is despite the fact that, in the UK alone, 70–80% of what has been built by 2010, is estimated to continue to exist for a number of decades to come: including the years 2020 and 2050 (the two main temporal deadlines in the Climate Change Act, 2008). In addition, this existing building stock is subject to obsolescence (both climate change-induced and non-climate change-associated) which in turn compromises sustainability. Thus, there are three notions that appear to be interwoven, i.e. Obsolescence, Climate Change, and Sustainability: the question is whether BIM can be exploited to address these. There has been only limited research work to explore the possible influence of BIM upon obsolescence, climate change, and sustainability as individual issues,and none reported, to-date, in terms of an approach to their collective consideration. This paper conceptually explores how BIM can be related with all three crucial notions simultaneously as well as discretely. It is argued that such studies can be particularly valuable in the face of escalating pressures in terms of future obsolescence risks, overwhelming evidence of climate change, and escalating sustainability agendas. The paper reviews current work that relates state-of-the-art BIM to the three notions, both separately and collectively, and thereby delineates the potential for BIM to play a role in addressing the three issues simultaneously

CONCURRENT MULTI-PART MULTI-EVENT DESIGN REFRESH PLANNING MODELS INCORPORATING SOLUTION REQUIREMENTS AND PART-UNIQUE TEMPORAL CONSTRAINTS

Technology obsolescence, also known as DMSMS (Diminishing Manufacturing Sources and Material Shortages), is a significant problem for systems whose operational life is much longer than the procurement lifetimes of their constitute components. The most severely affected systems are sustainment-dominated, which means their long-term sustainment (life-cycle) costs significantly exceed the procurement cost for the system. Unlike high-volume commercial products, these sustainment-dominated systems may require design refreshes to simply remain manufacturable and supportable. A strategic method for reducing the life-cycle cost impact of DMSMS is called refresh planning. The goal of refresh planning is to determine when design refreshes should occur (or what the frequency of refreshes should be) and how to manage the system components that are obsolete or soon to be obsolete at the design refreshes. Existing strategic management approaches focus on methods for determining design refresh dates. While creating a set of feasible design refresh plans is achievable using existing design refresh planning methodologies, the generated refresh plans may not satisfy the needs of the designers (sustainers and customers) because they do not conform to the constraints imposed on the system. This dissertation develops a new refresh planning model that satisfies refresh structure requirements (i.e., requirements that constrain the form of the refresh plan to be periodic) and develops and presents the definition, generalization, synthesis and application of part-unique temporal constraints in the design refresh planning process for systems impacted by DMSMS-type obsolescence. Periodic refresh plans are required by applications that are refresh deployment constrained such as ships and submarines (e.g., only a finite number of dry docks are available to refresh systems). The new refresh planning model developed in this dissertation requires 50% less data and runs 50% faster than the existing state-of-the-art discrete event simulation solutions for problems where a periodic refresh solution is required

The resilience of asset systems to the operational risk of obsolescence: using fuzzy logic to quantify risk profiles

This thesis sets out to explore possible methodologies to enable proactive obsolescence management for end users within the Built Environment. Obsolescence has shown to be a growing operational and financial risk as technology is further embedded into our buildings, seeking enhanced performance and connectivity. Obsolescence directly impacts the supportability of an asset system, manifesting into obsolescence-driven investments, which are typically managed reactively causing lifecycle costing complications. Gaps within academic literature and industry guidance have been identified herein and will be directly addressed by the research questions. The challenge of researching into obsolescence surrounds the commercial value of the required datasets, requiring a novel methodology to address the research problem. Further to this, the multi-stakeholder nature of supply chains, along with the unknown nature of obsolescence, has created a level of ambiguity within the datasets. Fuzzy Logic was adopted, above other options, to create an Obsolescence Impact Tool (OIT) that would enable the user to quantify the risk profile of obsolescence within asset systems. This model, along with an enhanced Obsolescence Assessment Tool (OAT), were both developed and tested within a two-year case study environment. Additional research questions were answered by analysing the reverse engineered original equipment manufacturers (OEM) sales catalogues. Through the combination of both the results from OIT and OAT, along with the analysis of OEM catalogues, a visualisation of the resilience of asset systems in respect to obsolescence is presented. The findings found herein provide evidence for the use of OIT and OAT for industrial application through the insights provided by data-driven models. The two models formulate a methodology that enables decision-making and proactive obsolescence management under uncertainty. The results of the OEM analysis provide explicit evidence that can immediately be used by the reader to enhance their obsolescence management plan (OMP). Evidence of the impact of sales strategies and how an end-user could utilise and reverse engineer the findings, hold potential for all Facilities Management teams. The findings culminate in a wide range of contributions that further the understanding of obsolescence within the Built Environment and importantly bridge some of the existing gaps. The Future Works chapter covers both observations made by the author and alternative methodologies that would provide further insight i.e. Type 2 Fuzzy Sets, Adaptive Learning Techniques, and Markov Chains

Scheduling based optimization in software defined radio and wireless networks

The objective of this work is to enable dynamic sharing of software-defined radio (SDR) transceivers through the concepts of hardware virtualization and real-time resource management. SDR is a way to build a digital radio that consists of a software back-end for digital signal processing (DSP) and an analog front-end transceiver for waveform generation and reception. This work proposes the use of a virtualization layer to decouple back-end SDR software from front-end transceivers. With this arrangement, front-ends are said to be virtualized, and it becomes possible to share a limited number of front-ends among many SDR back-ends through different multiplexing techniques. In the first work, the hardware/software infrastructure needed for such a system is explored. An intelligent resource management algorithm is presented that demonstrates a potential increase in the number of supported SDR back-ends. The second work presents an exploration of this system\u27s application to aircraft telemetry systems and the potential improvements to reliability. The work includes a reliability model for virtualized SDR aircraft telemetry systems as well as simulations demonstrating changes in performance as hardware fails. In the final work, an improved resource management algorithm based on Markov decision process (MDP) is proposed. This approach addresses concerns wireless regulatory agencies and standards bodies may raise regarding performance degradation caused by sharing transceivers. The process of sharing transceivers causes service disruptions to occur whenever the instantaneous demand for front-ends exceeds capacity. This MDP approach provides a feasibility test and a guarantee that all SDRs can stay within their respective wireless specifications. The proposed technique guarantees Pareto efficient distribution of resources. To make this approach possible, a connection is established between dynamic transceiver sharing and equivalent interference --Abstract, page iv

Considering stakeholders’ preferences for scheduling slots in capacity constrained airports

Airport slot scheduling has attracted the attention of researchers as a capacity management tool at congested airports. Recent research work has employed multi-objective approaches for scheduling slots at coordinated airports. However, the central question on how to select a commonly accepted airport schedule remains. The various participating stakeholders may have multiple and sometimes conflicting objectives stemming from their decision-making needs. This complex decision environment renders the identification of a commonly accepted solution rather difficult. In this presentation, we propose a multi-criteria decision-making technique that incorporates the priorities and preferences of the stakeholders in order to determine the best compromise solution