Investigation on Multi-Criteria Decision Making Methods Application in Sustainable Product Design

Background: Integrating sustainability development' aspects in the design process is becoming, a growth area in companies. Consequently, sustainable product design has to consider the different aspects of sustainability throughout its life cycle phases in addition of other requirements. This integration is becoming more complicated due the difficulty of managing the constraints and alternatives related to the product and stakeholders needs. This study aims to highlights the most used Multi-Criteria Decision Making (MCDM) tools and methods used in sustainable product design process. Contribution: Product design process involves interesting decisional tasks such as the choice of materials, standard parts, technical solutions. Hence, the contribution of this work is to help designer to adopt relevant MCDM tools and methods that can be integrated to other tools to facilitate and to justify their decisional tasks. Method: Several methods have been affected to solve the problems related to this complexity such as MCDM. A literature review was conducted based on Siencedirect and GoogleScholar articles databases. After filtering more than 200 articles only 62 articles were considered to analyze the correlation between sustainable product design and MCDM. Results: Classified MCDM use according to the type of choices to achieve SPD goals. This paper allowed us to find matches between MCDM methods and SPD problem. The majority of case studies result show that a large portion of sustainable design methods, techniques, and tools are applied to the sustainable product’ along its different life cycle phases Conclusion: It is noticed that the use of MCDM methods are an important outcome in the sustainable product design process and deeply helps designers to make suitable choices. Also, several matches relating MCDM, other methods and sustainable product design sphere are discusse

Tinjauan Pustaka Sistematis Penerapan Quality Function Deployment di Industri Manufaktur

Quality Function Deployment (QFD) is a tool or planning instrument that is used to provide an overview of customer desires which are then translated into strategic stages to produce products or services whose characteristics are in accordance with customer wishes. The advantage of this method approach is that the level of customer satisfaction can be explained through data, so that improving the quality of services or products and periodic evaluations to correct deficiencies can be carried out in accordance with the customer's assessment. Many studies using the QFD method are carried out by the industry. This literature review aims to analyze the advantages of the QFD method for increasing customer satisfaction in the manufacturing industry. The method used is the Systematic Literature Review. This article involves a study review of 24 articles related to the application of QFD in the manufacturing industry. The study was conducted using the Google Schoolar database. The articles obtained were then summarized, classified, and comprehensively reviewed. This article expands the knowledge and study of the application of QFD in the manufacturing industry. The development of QFD in future research can be carried out in cross-fields that still have links. QFD results can be a tool for making improvements based on the needs or voice of the customer. Improvements made using the QFD method can increase customer satisfaction, increase profits and marketing, improve service quality, and improve product quality

An overview of fuzzy techniques in supply chain management: bibliometrics, methodologies, applications and future directions

Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM

A methodology for the design of quality assurance functional model and information system

In spite of all advances in computer, technologies, information processing, automation technologies, manufacturing processes, and the push for integration across all functional areas toward a totally integrated and automated manufacturing system, the suggestion is that quality assurance which covers all quality-based functions in the product-life cycle is often overlooked. In spite of the important role of quality information systems in achieving high quality processes little published research in this area is found in the literature. Study of the available relevant literature and the collection of data from manufacturing industries confirm that different manufacturing situations require different quality assurance systems, and this is evident from the proliferation of differing QA systems found in industry. There are however some common features both universal/or within different classes of industries. Accordingly an 'ISO-9000 based generic structural model incorporating these common quality based functions and their associated information requirements has been developed. This research further investigates and verifies those factors which may affect the design of a QAIS as a guide for designing Quality Assurance Information Systems for manufacturing business organisations. Realising that knowledge-based systems can provide a support environment for designing QAIS, this research also considers and, develops a KB Decision System for Designing Quality Information Systems (DSDQAIS). The DSDQAIS recommends the structure of a QAIS, in the form of an IDEFO model, appropriate to specific company profiles input by the user. Since the available software' applications and development tools which support the sub-systems run on a personal computer, the prototype of this system has also been developed and tested on PC. Recommendations for the further development of the system are given

Rethinking the risk matrix

So far risk has been mostly defined as the expected value of a loss, mathematically PL (being P the probability of an adverse event and L the loss incurred as a consequence of the adverse event). The so called risk matrix follows from such definition. This definition of risk is justified in a long term “managerial” perspective, in which it is conceivable to distribute the effects of an adverse event on a large number of subjects or a large number of recurrences. In other words, this definition is mostly justified on frequentist terms. Moreover, according to this definition, in two extreme situations (high-probability/low-consequence and low-probability/high-consequence), the estimated risk is low. This logic is against the principles of sustainability and continuous improvement, which should impose instead both a continuous search for lower probabilities of adverse events (higher and higher reliability) and a continuous search for lower impact of adverse events (in accordance with the fail-safe principle). In this work a different definition of risk is proposed, which stems from the idea of safeguard: (1Risk)=(1P)(1L). According to this definition, the risk levels can be considered low only when both the probability of the adverse event and the loss are small. Such perspective, in which the calculation of safeguard is privileged to the calculation of risk, would possibly avoid exposing the Society to catastrophic consequences, sometimes due to wrong or oversimplified use of probabilistic models. Therefore, it can be seen as the citizen’s perspective to the definition of risk

A green-lean-six sigma model for environmental performance in manufacturing organizations : a study of a developed and developing nation : a thesis presented in partial fulfilment of the requirement for the degree of Doctor of Philosophy in Engineering Management, School of Food and Advanced Technology, Massey University, Auckland, New Zealand

Table 2.2 (=Kumar et al 2016) was removed for copyright reasonsManufacturing organizations continue to face environmental challenges including greenhouse gas (GHG) emissions, large-scale energy consumption, and solid and liquid waste generation contributing to climate change. While emerging environmental concerns are serious challenges for discrete and process industries in both developed and developing countries, the impact of these issues is more significant for the process industry due to their high energy requirements, GHG emissions, and lack of application of operational strategies. Green-lean-six sigma (GLSS) is recognized as a promising operational and environmental improvement strategy for minimizing waste and conserving resources in manufacturing organizations. However, scant attention has been paid to examining this strategy in addressing the environmental concerns, and in particular, investigating its application between developed and developing nations. The aim of this study is to examine the drivers, enablers, environmental outcomes, and critical success factors (CSFs) of a GLSS strategy in a developed country (New Zealand) and developing country (Pakistan) context in the manufacturing industry. This study draws on the natural resource-based view, institutional theory-based view, and intellectual capital-based view to understand the execution of this strategy and develops a GLSS model for improving the environmental performance in manufacturing organizations. A qualitative research methodology is adopted with semi-structured interviews using the case study approach. In the first phase, a preliminary study is undertaken with lean six sigma and environmental consultants from New Zealand (NZ) and Pakistan (PK). In the second phase, the main study is conducted with senior corporate managers of two large-sized flexible packaging manufacturing companies in both NZ and PK who have implemented the green, lean, and six sigma strategies. This study highlights various internal operational and organizational drivers and external regulatory, market-driven, and society-oriented forces that prompt manufacturing companies to adopt a GLSS strategy. Numerous GLSS enablers for achieving environmental outcomes including waste and emission reduction, resource conservation and recycling, and environmental safety and compliance are revealed. Further, CSFs for the implementation of a GLSS approach comprising the strategic, operational, human resource, and external stakeholder-related elements are presented. By utilizing the results of the preliminary and the main study, a holistic GLSS model is developed for achieving environmental performance in manufacturing organizations, with significant theoretical and practical implications

A Decision Support System for Benefits Realisation in Front End Design of Construction Projects in Dynamic Contexts

There is an increasing interest in the performance of construction projects, focussing on measurable value delivery. This research proposes a novel decision support system to support Front End Design (FED) decision making in addressing continuing value constraints in the delivery of project benefits. Stakeholder involvement and interests in projects that impact on project requirements understanding and management often means competing and sometimes conflicting requirements. However, projects now face increasing expectations to cope with emergent needs, which adds to uncertainty in the design process. As a result, there are continuing challenges in understanding and measuring project performance in terms of derived benefits. Increasingly, research points to the need for new understanding of FED processes on account of their vital contribution to value generation throughout the project life cycle. Much of current design practice however relies on qualitative explanatory/rationalistic methods to model uncertainty and predict changes in use cases in projects. The reliability of the approaches in the face of myriad, often conflicting and competing stakeholder interests in AEC design is increasingly under focus. This research adopts a mixed-methods approach in developing, validating and evaluating the proposed system in two case study project contexts for comparative assessment of the modelling results. The research formalises a new decision system (DESIDE), in exploring mathematical modelling based on Bayesian probabilistic models and proposes a new system focussed on the utility of decision making in the realisation of project benefits. The research explores the use of probability theory and appropriate mathematical approaches in the management and modelling of requirements and uncertainty during design decision making. The research also explores the use of complementary requirements forecasting modelling in a holistic integrated modelling approach. The research contributes to knowledge through 1) the new decision system that presents new frontiers in empirical evaluation of FED Benefits Realisation, 2) presenting an integrated analytical modelling approach of project requirements modelling in FED with a focus on the full project lifecycle performance based on analytical utility assessments and cause-effect modelling and 3) presenting a new integrated forecast and uncertainty probabilistic modelling approach of requirements in FED to support benefits realisation in projects