Strategic Proactive Obsolescence Management Model

Meng, Xiaozhou; Thörnberg, Benny; Olsson, Leif

doi:10.1109/tcpmt.2014.2316212

Cited by 24 publications

(8 citation statements)

References 12 publications

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“…The most common approach for strategic management of DMSMS is design refresh planning (DRP). 3,33,34 DRP chooses the best (usually lowest life-cycle cost) mix of design refreshes and reactive management approaches. DRP is highly dependent on obsolescence forecasts and their associated quantitative uncertainties.…”

Section: Discussionmentioning

confidence: 99%

Forecasting technology and part obsolescence

Sandborn

2015

Proceedings of the Institution of Mechanical Engineers, Part B:

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Technology-centric products often contain parts, software, and materials that have procurement lives that end before the product they are in reaches the end of its life cycle. Life-cycle mismatches between parts and products, which is referred to as obsolescence, can result in large life-cycle costs for mission, safety, and infrastructure critical products, such as aircraft, medical, and military systems. Diminishing Manufacturing Sources and Materials Shortages is a type of obsolescence that describes the loss of the ability to purchase (or procure) a part (or its associated technology) from its original manufacturer. A key enabler for performing pro-active and strategic management of the life cycle of mission, safety, and infrastructure critical products is the ability to forecast when technologies and parts will become unavailable for purchase, that is, obsolete. This article reviews methods that are used to forecast obsolescence, focusing on long-term forecasting used to predict the obsolescence dates for technologies and electronic parts.

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Section: Discussionmentioning

confidence: 99%

Forecasting technology and part obsolescence

Sandborn

2015

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Product life evolution was simulated by [24] using stochastic dynamic programming to make decisions with a Markov decision process. Multiple other studies tried to solve the obsolescence resolution problem using different techniques such as the restless bandit model and Markov decision process [25], integer programming [26], graph theory and mixed linear programming [27]. The limitation of the previous research is that it is costoriented and considers only two resolution strategies (last-time buy and redesign) from all resolution profiles, ignoring then the sustainable dimension of the problem.…”

Section: Literature Reviewmentioning

confidence: 99%

A Sustainable Multicriteria Decision Framework for Obsolescence Resolution Strategy Selection

et al. 2021

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Parts obsolescence has an important impact on the product life cycle, the manufacturing system and the environment leading to operational, logistical, reliability and cost implications. While current resolution models are cost-oriented, multiple studies have revealed that technological obsolescence is strongly involved in the electronic waste problem. In this study, based on academic literature and expert opinions, a sustainable decision framework for obsolescence resolution strategy (ORS) selection is proposed. It consists of economic, environmental, social and technological dimensions, integrating a total of fifteen criteria. Multicriteria decision-making (MCDM) methods are suggested to select the most sustainable solution. A case study was performed where the criteria weights and the alternatives performance were judged by five experts from the fields of environment, economy, human resources and obsolescence and operations management. Results from different MCDM methods were compared to the actual decision to evaluate their effectiveness. Using the suggested framework improved the decision process as integrating sustainability had a drastic impact on the selected strategy and consequently on the company’s performance. In addition to its managerial insights, this paper provides a new research perspective to sustainable and robust obsolescence management to effectively handle the increasing number and severity of obsolete components.

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“…Raza et al (2017) citam o impacto negativo do envelhecimento do inventário em um estudo de caso na indústria automotiva. Meng et al (2014) apresentaram um modelo matemático proativo de gerenciamento de obsolescência para sistemas de longa vida útil.…”

Section: Fundamentação Teóricaunclassified

Abordagem para Seleção de Variáveis Preditivas no Contexto de Controle de Inventários

Burgel

Anzanello

2018

R. Gest. Industr.

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A obsolescência de estoques é um fenômeno de destaque nas organizações, demandando o uso de métodos que identifiquem o inventário excessivo antes dele tornar-se obsoleto. Este artigo propõe um método para selecionar variáveis independentes em modelos de regressão preditivos com vistas à projeção do inventário ao longo do tempo, com o objetivo de reduzir o risco de obsolescência futuro. A abordagem proposta possui cinco passos, sendo os quatro primeiros dedicados à identificação dos fatores que contribuem para a obsolescência do inventário, a classificação do estoque em categorias e faixas de idade, a seleção de variáveis em contexto de PLS, a modelagem de regressão para projeção da idade do inventário ao longo do tempo e a definição de diretrizes para redução do risco de obsolescência. O quinto passo do método utiliza o conceito do ciclo PDCA buscando a melhoria contínua do processo e dos resultados. Na aplicação em uma indústria de bens de consumo, o método previu com precisão superior a 95% o montante do inventário por faixa de idade em um horizonte de seis meses.

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Strategic Proactive Obsolescence Management Model

Cited by 24 publications

References 12 publications

Forecasting technology and part obsolescence

Forecasting technology and part obsolescence

A Sustainable Multicriteria Decision Framework for Obsolescence Resolution Strategy Selection

Abordagem para Seleção de Variáveis Preditivas no Contexto de Controle de Inventários

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