An integrated expert weight determination method for design concept evaluation

Research on the evaluation of green suppliers of high energy-consuming enterprises--based on rough number-grey correlation TOPSIS method

With the Goal-Establishment of "carbon compliance" and "carbon neutrality", enterprises should upgrade "green development" to a strategic position and implement it through all aspects of business operations. Green supplier selection is the initial phase of supply chain management, therefore a green supplier evaluation system is needed to achieve green development. Based on a literature analysis, We selected 45 metrics as candidates for evaluating suppliers. Then through expert interviews, some indicators were revised and supplemented, and finally a green supplier evaluation index system for high energy-consuming enterprises was constructed. A unique aspect of this paper is the introduction of rough number theory into the supplier evaluation process to improve the indicator assignment and the grey correlation TOPSIS method, which optimizes the processing of uncertain semantic information in the evaluation process. The rough number-grey correlation TOPSIS supplier evaluation model developed in this paper has been verified to be applicable and stable in case studies and successfully implemented.

A novel MCDM approach for design concept evaluation based on interval-valued picture fuzzy sets

The assessment of design concepts presents an efficient and effective strategy for businesses to strengthen their competitive edge and introduce market-worthy products. The widely accepted viewpoint acknowledges this as a intricate multi-criteria decision-making (MCDM) approach, involving a multitude of evaluative criteria and a significant amount of data that is frequently ambiguously defined and subjectively influenced. In order to tackle the problems of uncertainty and fuzziness in design concept evaluation, our research creatively combines interval-valued picture fuzzy set (IVPFS) with an MCDM process of design concept evaluation. Firstly, this study draws on the existing relevant literature and the experience of decision makers to identify some important criteria and corresponding sub-criteria and form a scientific evaluation indicator system. We then introduce the essential operational concepts of interval-valued picture fuzzy numbers (IVPFNs) and the interval-valued picture fuzzy ordered weighted interactive averaging (IVPFOWIA) operator. Thirdly, an entropy weighting method based on IVPFS is proposed in this research to calculate the weights of criteria and sub-criteria, and based on this, an integrated IVPF decision matrix is further constructed based on the presented IVPFOWIA operator. Finally, the best design concept alternative is selected by applying the extended TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) approach with IVPFS. The IVPFS combined with improved MCDM method have been proven to be superior in complex and uncertain decision-making situations through experiments and comparative assessments. The information ambiguity in the evaluation of design concept is well characterized by our augmentation based on IVPFS.

A quantitative approach on environment-food nexus: integrated modeling and indices for cumulative impact assessment of farm management practices

Background

Best management practices (BMPs) are promising solutions that can partially control pollution discharged from farmlands. These strategies, like fertilizer reduction and using filter strips, mainly control nutrient (N and P) pollution loads in basins. However, they have secondary impacts on nutrition production and ecosystem. This study develops a method to evaluate the cumulative environmental impacts of BMPs. It also introduces and calculates food's environmental footprint (FEF) for accounting the total environmental damages per nutrition production.

Methods

This study combines the soil and water assessment tool (SWAT) for basin simulation with the indices of ReCiPe, a life cycle impact assessment (LCIA) method. By these means, the effectiveness of BMPs on pollution loads, production yields, and water footprints (WFs) are evaluated and converted as equivalent environmental damages. This method was verified in Zrebar Lake, western Iran. Here, water consumption, as WFs, and eutrophication are the main indices that are converted into equivalent health and ecological impairments. Two methods, entropy and environmental performance index (EPI), are used for weighting normalized endpoints in last step.

Results

Results showed that using 25-50% less fertilizer and water for irrigation combined with vegetated filter strips reduce N and P pollution about 34-60% and 8-21%, respectively. These can decrease ecosystem damages by 5-9% and health risks by 7-14%. Here, freshwater eutrophication is a more critical damage in ecosystem. However, using less fertilizer adversely reduces total nutrition production by 1.7-3.7%. It means that BMPs can decline total ecological damages and health risks, which threatens nutrition production. FEF presents a tool to solve this dilemma about the sustainability of BMPs. In the study area, a 4-9% decrease in FEF means that BMPs are more environmental friendly than nutrition menacing. Finally, this study concludes that SWAT-ReCiPe with FEF provides a quantitative framework for environment-food nexus assessment. However, due to the uncertainties, this method is recommended as a tool for comparing management strategies instead of reporting certain values.

A comprehensive mortise and tenon structure selection method based on Pugh's controlled convergence and rough Z-number MABAC method

Mortise and tenon joints are widely used in the building and furniture industries because of their excellent mechanical and eco-friendly properties. In real-life cases, there are usually many available alternative structures for a joint area, it is a challenge to select a proper structure from massively available alternatives. This paper aims to select a proper multiple attribute decision-making method based on massive alternatives and unreliable, uncertain and subjective information. Pugh's controlled convergence, rough number, Z-number, consistency theory and Shannon entropy are integrated and proposed an improved rough Z-number Multi-Attributive Border Approximation Area Comparison (MABAC) method. Firstly, Pugh's controlled convergence is a selection method, simple and rapid, presented in the first phase to eliminate most of the alternatives. In the second phase, an integrated method is proposed. The consistency theory, distance measurement and the Z-number are initially aggregated to calculate the expert weight. The entropy method is then presented to determine the criteria weight. The alternatives are then ranked and the optimal mortise and tenon joint is selected based on the rough Z-number MABAC method. A real-life case is presented, and the proposed method is implemented in the joint of a bucket cabinet. Finally, the efficiency and effectiveness of the proposed method are proved by the case, sensitivity analysis and related comparisons.

An MAGDM method for design concept evaluation based on incomplete information

Design concept evaluation is a huge challenge in the R&D stage of new product development. The information in the assessments often depends on the decision-makers' individual preferences. However, sometimes the decision-makers cannot give precise and complete information because it is very difficult for them to be familiar with all the criteria. In this situation, an incomplete information decision-making matrix is established. In this paper, decision-making methods based on incomplete information are compared in the literature review. Incomplete information determination method using trust mechanism is proved as a proper way to solve this problem, and the missing information are computed based on the alternatives However, in design concept evaluation, experts commonly provide their preferences using linguistic words according to the different attributes. Hence, we propose a three-step Multiple Attributes Group Decision-making (MAGDM) method where the missing value are determined by attributes. In step one, a data repairing method is proposed based on trust theory. After that, in step two, a comprehensive weight determination method combining AHP and entropy is proposed to obtain the weight of index attributes. Finally, the Rough-TOPSIS method is applied in the design scheme ranking step. In the case study, the proposed method is implemented in a tourism product design process to show its effectiveness.

A novel integrated MADM method for design concept evaluation

Design concept evaluation plays a significant role in new product development. Rough set based methods are regarded as effective evaluation techniques when facing a vague and uncertain environment and are widely used in product research and development. This paper proposed an improved rough-TOPSIS method, which aims to reduce the imprecision of design concept evaluation in two ways. First, the expert group for design concept evaluation is classified into three clusters: designers, manufacturers, and customers. The cluster weight is determined by roles in the assessment using a Multiplicative Analytic Hierarchy Process method. Second, the raw information collection method is improved with a 3-step process, and both design values and expert linguistic preferences are integrated into the rough decision matrix. The alternatives are then ranked with a rough-TOPSIS method with entropy criteria weight. A practical example is shown to demonstrate the method's viability. The findings suggest that the proposed decision-making process is effective in product concept design evaluation.

Datasets of skills-rating questionnaires for advanced service design through expert knowledge elicitation

This article presents a dataset of service design skills which service design experts value as important requirements for design team members. Purposive sampling and a chain referral approach were used to recruit appropriate experts to conduct questionnaire-based research. Using the analytical hierarchy process (AHP), pairwise skills-rating questionnaires were designed to elicit the experts’ responses. The resulting dataset was processed using AHP algorithms programmed in R programming language. The transparent data and available codes of the research may be reused by design practitioners and researchers for replication and further analysis. This paper offers a reproduceable research process and associated dataset for conducting multiple-criteria decision analysis with expert purposive sampling.