Current practice and challenges towards handling uncertainty for effective outcomes in maintenance

The combination of viable heuristic attributes with statistical measurements presents significant challenges in industrial maintenance for complex assets under through-life service contracts. Techniques to obtain and process heuristic attributes raise numerous uncertainties which often go undefined and unmitigated. A holistic view of these uncertainties may improve decision-making capabilities and reduce maintenance costs and turnaround time. It is therefore necessary to identify and rank factors that influence uncertainties originating from challenges in the above context. This, along with an identification of who contributes to such challenges and current practice to handle them, sets the focus for this study. The influence of 32 categorised factors on uncertainty is assessed through a questionnaire completed by nine experienced maintenance managers from a leading defence company. The pedigree approach is applied to score validity of respondents’ answers according to their experience and job role to normalise scores. Results are discussed in interviews with respondents along with current practice in and ways to improve uncertainty assessment. Scores are weighted through the Analytical Hierarchy Process (AHP) in order to identify the most influential factors on uncertainty in maintenance. The analysis revealed that these include: intellectual property rights (IPR), maintainer performance, quality of information, resistance to change, stakeholder communication and technology integration. These are verified with 40 practitioners from various industrial backgrounds. From the interviews, it is deemed that a holistic view of heuristic and statistical attributes ultimately allows for more accomplished decision-making but requires trade-offs between quality and cost over the asset’s life cycle

Decision-making methods in engineering design: a designer-oriented approach

The use of decisional methods for the solution of engineering design problems has to be tackled on a "human" viewpoint. Hence, fundamental is the identification of design issues and needs that become a designer oriented viewpoint. Decision-based methods are systematically classified in MCDM methods, Structured Design methods and Problem Structuring methods. The results are organised in order to provide a first reference for the designer in a preliminary selection of decision-based methods. The paper shows the heterogeneous use of decision-based methods, traditionally expected to solve only some specific design problems, which have been used also in different design contexts. Moreover, several design issues, which emerged from the review process, have been pointed out and discussed accordingly. This review provided useful results for the enlargement of the state of the art on Decision Based Design methods in engineering design contexts

Sustainable and agile manufacturing outsourcing partner selection: a literature review

[EN] Outsourcing to third party to manage non-core activities helps the firm to focus on core activities. Manufacturing firms are outsourcing product development, manufacturing, logistics, customer care etc. to enhance production capacity and flexibility, and to reduce operational costs, which in turn can improve profitability and competitive advantage of the enterprise. Sustainability in operations and supply chain is gaining momentum due to increased global environmental concern, pressures from consumers and communities, and enforced regulations. Volatile and uncertain business environment necessitates the adoption of agility and flexibility to effectively manage manufacturing and supply chain. Globalisation has made the market very competitive and hence manufacturing firms are adopting manufacturing outsourcing to third parties. Selecting a sustainable and agile manufacturing outsourcing partner (MPS) is crucial as it will improve sustainability, efficiency, and effectiveness of the supply chain and competitive advantage to the firm. Detailed literature review on sustainable and agile manufacturing outsourcing partner selection has been carried out from EBSCO data base and Goggle scholar. Selection criteria used are classified into agile, operational, economic, environmental and social. The techniques use are mostly multi criteria decision making methods (MCDM) while few have adopted programming techniques. Discussion, implication and the scope of future work is also provided.Akhtar, M. (2022). Sustainable and agile manufacturing outsourcing partner selection: a literature review. International Journal of Production Management and Engineering. 10(2):143-158. https://doi.org/10.4995/ijpme.2022.1680714315810

Data-Driven Decision Analysis on the Selection of Course Programmes with AHP-TOPSIS Model

The course selection has become a favorite issue among the students who pursue their tertiary study in university nowadays. This is because there are a lot of course programmes offered in this knowledge-based education system. Besides that, other factors such as the financial problem, motivation, self-interest, moral support from friends and family are important criteria in the selection of course programmes. The objective of this study is to propose a data-driven conceptual framework to determine the student preference in the selection of course programmes with Analytic Hierarchy Process Technique for Order of Preference by Similarity to Ideal Solution (AHP-TOPSIS) model. Moreover, this study also aims to determine the priority of the decision criteria that influence the selection of course programmes among the students. In this study, the target respondents are the science stream students from Universiti Tunku Abdul Rahman, Malaysia who provide the inputs as data-driven decision analysis on the selection of course programmes. The results of this study show that medical science is the most preferred course programmes among the students followed by engineering, science and lastly information system. On the other hand, career prospect has been identified as the most concerned decision criterion by the student in the selection of course programmes. This study is significant because it helps to determine the most preferred course programme as well as the most influential criteria in the selection of course programmes among the students with the proposed conceptual framework based on AHP-TOPSIS model

Lean, agile, resilient and green supply chain management interoperability assessment methodology

Dissertação para obtenção de grau de Mestre em Engenharia e Gestão Industrial (MEGI)Supply Chain Management has become a tactic asset for the current global competition situation. Innovative strategies such as Lean, Agile, Resilient and Green emerged as a response, requiring high levels of cooperation and of great complexity. However, the strategic alignment of operations with partners in supply chains is affected by lack of interoperability. The present work provides a framework to enhance SC competitiveness and performance by assessing interoperable SCM Practices applied in automotive industry. Through a pragmatic interoperability approach, this methodology describes in detail the form of application using analytical hierarchical process (AHP) and Fuzzy sets as support decision making models, ensuring a systematic approach to the analysis of interoperability with appropriate criteria for assessment of situations that require high levels of collaboration between partners. Through a case study in a Portuguese automaker, it was possible to test the methodology and analyse which areas lack interoperability in the implementation of SCM practices

Dynamic small-series fashion order allocation and supplier selection: a ga-topsis-based model

The fashion industry is currently confronted with significant economic and environmental challenges, necessitating the exploration of novel business models. Among the promising approaches is small series production on demand, though this poses considerable complexities in the highly competitive sector. Traditional supplier selection and production planning processes, known for their lengthy and intricate nature, must be replaced with more dynamic and effective decision-making procedures. To tackle this problem, GA-TOPSIS hybrid model is proposed as the methodology. The model integrates Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) evaluation into the fitness function of Genetic Algorithm (GA) to comprehensively consider both qualitative and quantitative criteria for supplier selection. Simultaneously, GA efficiently optimizes the order sequence for production planning. The model's efficacy is demonstrated through implementation on real orders, showcasing its ability to handle diverse evaluation criteria and support supplier selection in different scenarios. Moreover, the proposed model is employed to compute the Pareto front, which provides optimal sets of solutions for the given objective criteria. This allows for an effective demand-driven strategy, particularly relevant for fashion retailers to select supplier and order planning optimization decisions in dynamic and multi-criteria context. Overall, GA-TOPSIS hybrid model offers an innovative and efficient decision support system for fashion retailers to adapt to changing demands and achieve effective supplier selection and production planning optimization. The model's incorporation of both qualitative and quantitative criteria in a dynamic environment contributes to its originality and potential for addressing the complexities of the fashion industry's supply chain challenge

Framework for benchmarking online retailing performance using fuzzy AHP and TOPSIS method

Due to increasing penetration of internet connectivity, on-line retail is growing from the pioneer phase to increasing integration within people's lives and companies' normal business practices. In the increasingly competitive environment, on-line retail service providers require systematic and structured approach to have cutting edge over the rival. Thus, the use of benchmarking has become indispensable to accomplish superior performance to support the on-line retail service providers. This paper uses the fuzzy analytic hierarchy process (FAHP) approach to support a generic on-line retail benchmarking process. Critical success factors for on-line retail service have been identified from a structured questionnaire and literature and prioritized using fuzzy AHP. Using these critical success factors, performance levels of the ORENET an on-line retail service provider is benchmarked along with four other on-line service providers using TOPSIS method. Based on the benchmark, their relative ranking has also been illustrated

Operational framework for healthcare supplier selection under a fuzzy multi-criteria environment

PURPOSE: This paper studies how a logistics service provider managing the suppliers for several hospitals can innovatively improve the supplier selection process. The paper examines the attribute set for healthcare supplier selection such as response time, reliability, stock quantity, in order to realize optimal cube utilization, cost, and customer satisfaction. This operational framework developed can help a logistics service provider in supplier order management based on the selected criteria set, criteria weight calculation, and supplier ranking under a fuzzy multi-criteria decision making (MCDM) environment. DESIGN/METHODOLOGY/APPROACH: We adopt a multi-objective decision making approach based on three main criteria of service, cost, and disruption risk. The following modelling approaches are used – (i) the criteria weight are found using fuzzy AHP, and (ii) the ranking of the suppliers are found through fuzzy TOPSIS. FINDINGS: Sometimes a logistics service provider needs to include multiple suppliers for one product instead of the current single supplier policy, in order to share the risks especially when dealing with public health emergencies and uncertainty in disruptions. VALUE: This is a practical industrial problem dealing with various facets of MCDM being applied on actual data, so as to bring to bear the actual challenges of using MCDM in dealing with healthcare supplier management. RESEARCH LIMITATIONS/IMPLICATIONS: Some future extensions and current limitations of this work will include the sole suppliers, namely, suppliers who are exclusive providers of certain unique products mandated by the healthcare regulators, and to include the effects of shelf life and perishability into the products such as the biodegradable sutures. PRACTICAL IMPLICATIONS: This study can help the healthcare logistics service provider to use data judiciously to select and manage the suppliers optimally, without the unnecessary incurrence of buffer stock at the warehouse, which can lead a high degree of obsolescence