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Processes
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Advances in Sustainable Supply Chains
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Advances in Sustainable Supply Chains

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Sustainable Processes".

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 73821

Special Issue Editors

Prof. Dr. Taesu Cheong

E-Mail Website
Guest Editor
Department of Industrial and Management Engineering, Korea University, Seoul 02841, Republic of Korea
Interests: supply chain management; supply chain; sustainable logistics; decision making under uncertainty; value of information; intelligent transportation; systems; healthcare
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Sang Hwa Song

E-Mail Website
Guest Editor
Graduate School of logistics, Incheon National University, Incheon 22012, Korea
Interests: last-mile logistics; e-commerce fulfillment; smart logistics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Supply chain management is an indispensable part of a business’s sustainability program. Knowing the level of environmental, social, and economic impact and viability of suppliers and customers is becoming increasingly common as all industries move towards a more sustainable future. Indeed, companies are striving to operate in a more sustainable manner. In the meantime, sustainability has been one of the key drivers of technological innovation, and much of the increase in business efficiency over recent years has been achieved with the help of advanced technologies such as IoT/RFID, big data, artificial intelligence, blockchain, and so on. While the potential of such technologies is enormous, so are the challenges involved in seamlessly integration across organizations in a sustainable manner.

In this context, this Special Issue on "Advances in Sustainable Supply Chains" aims to incorporate recent innovative methodologies and models for leading and moving toward sustainability in logistics and supply chain management. Topics include, but are not limited to, the following:

  • Sustainable supply chain management with applications
  • Robust and resilient supply chain design and operation
  • Smart and sustainable manufacturing systems and technologies
  • Sustainable production and inventory management
  • Sustainable distribution management
  • Sustainable logistics networks design
  • Green and sustainable logistics and transportation
  • Analytical models for sustainable supply chain
  • Green and close-loop logistics and supply chain management
  • Big data management and IoT for sustainable supply chains
  • Sustainable humanitarian logistics and supply chain management

This Special Issue welcomes full research articles, short communications, conceptual papers, literature reviews, and case studies (descriptive papers illustrating a particular practice or a solution to a managerial problem). Papers using analytical methods or mathematical modeling developments are particularly interesting for this Special Issue.

Prof. Dr. Taesu Cheong
Prof. Dr. Sang Hwa Song
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainability
  • logistics
  • transportation
  • supply chain management
  • big data
  • IoT
  • smart manufacturing
  • green supply chain
  • sustainable production
  • humanitarian logistics

Published Papers (13 papers)

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Research

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21 pages, 6515 KiB  
Article
A Process-Based Modeling Method for Describing Production Processes of Ship Block Assembly Planning
by Dongsu Jeong, Dohyun Kim, Taihun Choi and Yoonho Seo
Processes 2020, 8(7), 880; https://0-doi-org.brum.beds.ac.uk/10.3390/pr8070880 - 21 Jul 2020
Cited by 7 | Viewed by 8358
Abstract
Ship block assembly planning is very complex due to the various activities and characteristics of ship production. Therefore, competitiveness in the shipbuilding industry depends on how well a company operates its ship block assembly plan. Many shipbuilders are implementing various studies to improve [...] Read more.
Ship block assembly planning is very complex due to the various activities and characteristics of ship production. Therefore, competitiveness in the shipbuilding industry depends on how well a company operates its ship block assembly plan. Many shipbuilders are implementing various studies to improve their competitiveness in ship block assembly planning, specifically regarding technology usage, such as modeling and simulation (M&S) and Cyber-Physical Systems (CPS). Although these technologies are successfully applied in some production planning systems, it is difficult to tailor ship production planning systems with flexibility due to unexpected situations. Providing a flexible plan for these production planning systems requires a way to describe and review the organic relationships of ship production processes. In this research, a process-based modeling (PBM) method proposes a novel approach to describing the production process of ship block assembly planning by redefining production information based on changing instructions. The proposed method consists of four modeling steps. The first creates a unit model, which includes the products, processes, and resource information for the block. The second designs an integrated network process for linking unit models according to the bill of materials (BOM). The third creates a process-based model that describes the production processes by combining unit models. The fourth generates a simulation model by applying a Petri-net to the process-based model, which analyzes the productivity of the ship’s block assembly processes. PBM identifies the assembly process’ interrelationship and shows that productivity can be reviewed to uncover ship production problems. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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19 pages, 1149 KiB  
Article
Capacitated Lot-Sizing Problem with Sequence-Dependent Setup, Setup Carryover and Setup Crossover
by Jangha Kang
Processes 2020, 8(7), 785; https://0-doi-org.brum.beds.ac.uk/10.3390/pr8070785 - 05 Jul 2020
Cited by 1 | Viewed by 3073
Abstract
Since setup operations have significant impacts on production environments, the capacitated lot-sizing problem considering arbitrary length of setup times helps to develop flexible and efficient production plans. This study discusses a capacitated lot-sizing problem with sequence-dependent setup, setup carryover and setup crossover. A [...] Read more.
Since setup operations have significant impacts on production environments, the capacitated lot-sizing problem considering arbitrary length of setup times helps to develop flexible and efficient production plans. This study discusses a capacitated lot-sizing problem with sequence-dependent setup, setup carryover and setup crossover. A new mixed integer programming formulation is proposed. The formulation is based on three building blocks: the facility location extended formulation; the setup variables with indices for the starting and the completion time periods; and exponential number of generalized subtour elimination constraints (GSECs). A separation routine is adopted to generate the violated GSECs. Computational experiments show that the proposed formulation outperforms models from the literature. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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23 pages, 1030 KiB  
Article
Introducing Risk Considerations into the Supply Chain Network Design
by Ernest Benedito, Carme Martínez-Costa and Sergio Rubio
Processes 2020, 8(6), 743; https://0-doi-org.brum.beds.ac.uk/10.3390/pr8060743 - 26 Jun 2020
Cited by 9 | Viewed by 7165
Abstract
Supply chains (SC) aim to provide products to the final customer at a certain service level. However, unforeseen events occur that impede supply chain objectives. SC Risk has been studied in the literature, providing frameworks and methodologies to manage SC failures. Nevertheless, more [...] Read more.
Supply chains (SC) aim to provide products to the final customer at a certain service level. However, unforeseen events occur that impede supply chain objectives. SC Risk has been studied in the literature, providing frameworks and methodologies to manage SC failures. Nevertheless, more efforts are needed to prevent hazardous and disruptive risks and their consequences. These risks must be considered during the process of designing a supply chain. Some methodological contributions concerning risk in the supply chain network design (SCND) are conceptual frameworks for mitigating SC disruptions, which suggest strategies and measures for designing robust and resilient SCs. Although such contributions are valuable, they do not indicate how to cope with risk when designing a SC. The main objective of this research is to describe a methodology aimed at including risk considerations into the SCND. Our proposal aims to be, on the one hand, a comprehensive approach that includes a risk identification and assessment procedure in each of the stages of the SCND process and, on the other hand, a tool for decision-making in SC design or redesign processes when SC risks need to be considered. The methodology proposed is an extension of a SCND methodology including risk considerations in order to improve the performance of the supply chains. A case study illustrates how the proposed methodological works, achieving the identification of SC risks already observed in previous works. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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24 pages, 1338 KiB  
Article
Supplier Selection for the Adoption of Green Innovation in Sustainable Supply Chain Management Practices: A Case of the Chinese Textile Manufacturing Industry
by Yun Yang and Ying Wang
Processes 2020, 8(6), 717; https://0-doi-org.brum.beds.ac.uk/10.3390/pr8060717 - 20 Jun 2020
Cited by 31 | Viewed by 5403
Abstract
Globally, increasing environmental issues are gaining attention to facilitate the adoption of green innovation for sustainable supply chain management (SSCM). Sustainable environmental practices have been well-considered in the literature; however, no study has focused on adopting green innovation practices for sustainable development. Thus, [...] Read more.
Globally, increasing environmental issues are gaining attention to facilitate the adoption of green innovation for sustainable supply chain management (SSCM). Sustainable environmental practices have been well-considered in the literature; however, no study has focused on adopting green innovation practices for sustainable development. Thus, environmental management authorities are putting pressure on industries to implement green innovation criteria for SSCM operations. Moreover, it is important to select traditional suppliers to transform its practices to that of sustainable supply chains in order to achieve the industry’s sustainable supply chain goals. In response, this research identified and analyzed the green innovation criteria for SSCM and then selected a supplier that could implement green aspects in the SSCM. This study developed an integrated multi-criteria decision making (MCDM) model using the fuzzy analytical hierarchy process (FAHP) and the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS). The objective of this study was to analyze suppliers to implement green innovation criteria for SSCM practices in the textile manufacturing companies of China. This study reviewed and identified three green innovation criteria and seventeen sub-criteria. Then, the FAHP technique was employed to analyze and rank green innovation criteria and sub-criteria. Finally, the FTOPSIS method was used to investigate and rank eight suppliers. The findings of the FAHP indicated that economic (EC) criteria were the most vital green innovation criteria in the SSCM. Furthermore, the FTOPSIS results revealed that supplier 5 was the most suitable supplier for implementing green innovation criteria in the SSCM. These findings will help managers, practitioners, and policymakers implement green innovation criteria in sustainable manufacturing supply chains. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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21 pages, 7996 KiB  
Article
Assessment of Supply Chain Agility to Foster Sustainability: Fuzzy-DSS for a Saudi Manufacturing Organization
by Ateekh Ur Rehman, Ayoub Al-Zabidi, Mohammed AlKahtani, Usama Umer and Yusuf Siraj Usmani
Processes 2020, 8(5), 577; https://0-doi-org.brum.beds.ac.uk/10.3390/pr8050577 - 13 May 2020
Cited by 13 | Viewed by 3955
Abstract
Supply chain agility and sustainability is an essential element for the long-term survival and success of a manufacturing organization. Agility is an organization’s ability to respond rapidly to customers’ dynamic demands and volatile market changes. In a dynamic business environment, manufacturing firms demand [...] Read more.
Supply chain agility and sustainability is an essential element for the long-term survival and success of a manufacturing organization. Agility is an organization’s ability to respond rapidly to customers’ dynamic demands and volatile market changes. In a dynamic business environment, manufacturing firms demand agility to be evaluated to support any alarming decision. Sustainability is an aspect to sustain collaboration, value creation, and survival of firms under a dynamic competitive business scenario. Agility is a capability that drives competitiveness to foster sustainability aspects. The purpose of this article is to consider and evaluate the supply chain behavior within the context of Saudi enterprises. The efficacy and relevance of this model were explored through a case study conducted in a Saudi dairy manufacturing corporation. Owing to the complexity and a large number of calculations that are required for evaluating the agility of the supply chain, a decision support system was proposed as a tool to assess the supply chain and identifying barriers to a strategic sustainable solution for a specific organizational target. The decision support system is extensive as it contains six separate agility enablers and ninety-three agility attributes for the supply chain. The assessment was carried out using a fuzzy multi-criteria method. It combines the performance rating and importance weight of each agile supply chain-enabler-attribute. To achieve and sustain local and global success, the case organization strove to become a major local and global manufacturer to satisfy its customers, reduce its time to market, lower its total ownership costs, and boost its overall competitiveness through improving its agility across supply chain activities to foster sustainability for a manufacturing organization located in Saudi Arabia. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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10 pages, 230 KiB  
Article
The Impact of Uncertainty Factors on the Decision-Making Process of Logistics Management
by Łukasz Marzantowicz
Processes 2020, 8(5), 512; https://0-doi-org.brum.beds.ac.uk/10.3390/pr8050512 - 26 Apr 2020
Cited by 3 | Viewed by 3661
Abstract
The article is a contribution to the discussion on the possibilities of effective logistic decisions under the conditions of uncertainty. Variable and unpredictable factors, which create the conditions of uncertainty, not only directly affect logistic processes (positive or negative impact), but can also [...] Read more.
The article is a contribution to the discussion on the possibilities of effective logistic decisions under the conditions of uncertainty. Variable and unpredictable factors, which create the conditions of uncertainty, not only directly affect logistic processes (positive or negative impact), but can also be a determinant of making decisions. Logistics management, because it is referred to in the context of decision-making, is currently defined by the quality of management decisions taken, including factors which often constitute only partially quantifiable sets. The main goal of the article is to show the strength of the dependence between the occurrence of uncertainty factors and the type of decision. On the basis of decision-making theory, the types of decisions were defined, and then a set of factors that are most important for a given type of decision was selected. The results of the analysis allowed the strength of the influence of uncertainty factors on making logistics decisions to be determined. On this basis, a catalog of key decisions was selected, including decision types, and also the effects of decisions taken under uncertainty were determined. The study and the results of the analysis should be treated rather as a voice in the ongoing discussion. Due to the unpredictability of some uncertainty factors, the research field in the discussed problem remains open. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
16 pages, 1803 KiB  
Article
Systematic Boolean Satisfiability Programming in Radial Basis Function Neural Network
by Mohd. Asyraf Mansor, Siti Zulaikha Mohd Jamaludin, Mohd Shareduwan Mohd Kasihmuddin, Shehab Abdulhabib Alzaeemi, Md Faisal Md Basir and Saratha Sathasivam
Processes 2020, 8(2), 214; https://0-doi-org.brum.beds.ac.uk/10.3390/pr8020214 - 10 Feb 2020
Cited by 17 | Viewed by 2980
Abstract
Radial Basis Function Neural Network (RBFNN) is a class of Artificial Neural Network (ANN) that contains hidden layer processing units (neurons) with nonlinear, radially symmetric activation functions. Consequently, RBFNN has extensively suffered from significant computational error and difficulties in approximating the optimal hidden [...] Read more.
Radial Basis Function Neural Network (RBFNN) is a class of Artificial Neural Network (ANN) that contains hidden layer processing units (neurons) with nonlinear, radially symmetric activation functions. Consequently, RBFNN has extensively suffered from significant computational error and difficulties in approximating the optimal hidden neuron, especially when dealing with Boolean Satisfiability logical rule. In this paper, we present a comprehensive investigation of the potential effect of systematic Satisfiability programming as a logical rule, namely 2 Satisfiability (2SAT) to optimize the output weights and parameters in RBFNN. The 2SAT logical rule has extensively applied in various disciplines, ranging from industrial automation to the complex management system. The core impetus of this study is to investigate the effectiveness of 2SAT logical rule in reducing the computational burden for RBFNN by obtaining the parameters in RBFNN. The comparison is made between RBFNN and the existing method, based on the Hopfield Neural Network (HNN) in searching for the optimal neuron state by utilizing different numbers of neurons. The comparison was made with the HNN as a benchmark to validate the final output of our proposed RBFNN with 2SAT logical rule. Note that the final output in HNN is represented in terms of the quality of the final states produced at the end of the simulation. The simulation dynamic was carried out by using the simulated data, randomly generated by the program. In terms of 2SAT logical rule, simulation revealed that RBFNN has two advantages over HNN model: RBFNN can obtain the correct final neuron state with the lowest error and does not require any approximation for the number of hidden layers. Furthermore, this study provides a new paradigm in the field feed-forward neural network by implementing a more systematic propositional logic rule. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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22 pages, 3691 KiB  
Article
A Two-Stage Optimal Scheduling Model of Microgrid Based on Chance-Constrained Programming in Spot Markets
by Jiayu Li, Caixia Tan, Zhongrui Ren, Jiacheng Yang, Xue Yu and Zhongfu Tan
Processes 2020, 8(1), 107; https://0-doi-org.brum.beds.ac.uk/10.3390/pr8010107 - 14 Jan 2020
Cited by 4 | Viewed by 2437
Abstract
Aimed at the coordination control problem of each unit caused by microgrid participation in the spot market and considering the randomness of wind and solar output and the uncertainty of spot market prices, a day-ahead real-time two-stage optimal scheduling model for microgrid was [...] Read more.
Aimed at the coordination control problem of each unit caused by microgrid participation in the spot market and considering the randomness of wind and solar output and the uncertainty of spot market prices, a day-ahead real-time two-stage optimal scheduling model for microgrid was established by using the chance-constrained programming theory. On this basis, an improved particle swarm optimization (PSO) algorithm based on stochastic simulation technology was used to solve the problem and the effect of demand side management and confidence level on scheduling results is discussed. The example results verified the correctness and effectiveness of the proposed model, which can provide a theoretical basis in terms of reasonably coordinating the output of each unit in the microgrid in the spot market. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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27 pages, 2183 KiB  
Article
Optimization of the Technology Transfer Process Using Gantt Charts and Critical Path Analysis Flow Diagrams: Case Study of the Korean Automobile Industry
by Sangkon Lee and Olga A. Shvetsova
Processes 2019, 7(12), 917; https://0-doi-org.brum.beds.ac.uk/10.3390/pr7120917 - 03 Dec 2019
Cited by 8 | Viewed by 14654
Abstract
This research is focused on the technology transfer process in the automobile industry using project management tools. The aim of this research is the development of a technology-transfer model using Gantt charts and Critical Path Analysis flow diagrams to achieve a sustainable planning [...] Read more.
This research is focused on the technology transfer process in the automobile industry using project management tools. The aim of this research is the development of a technology-transfer model using Gantt charts and Critical Path Analysis flow diagrams to achieve a sustainable planning process in the global environment. To achieve this goal, the authors use Gantt charts and Critical Path Analysis flow diagrams. The hypothesis and three research questions are presented, which suggest a relationship between project management tools and the sustainable planning process of technology transfer. During the research, we use the case study of the Korean automobile industry as an excellent example of the technology-transfer process in global markets. A single project of technology transfer is discussed: the technology knowledge transfer from Korean headquarters to a Russian manufacturing subsidiary (Hyundai Motor Corporation). Quantitative data were collected through the open resources of the corporation; the qualitative data were analyzed through a case study and model parameter evaluation. The significant result that the combination of Gantt Charts and Critical Path Analysis flow diagrams methods improves the planning process for technology-transfer projects was found in this survey. It is noticed that (a) it is useful to apply project-management tools for technology transferring models; (b) Gantt Charts and Critical Path Analysis flow diagrams have a sustainable impact on technology transfer projects; and (c) critical paths and operational reserves in network diagrams help to optimize the planning process for technology transfer. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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19 pages, 1549 KiB  
Article
Game Analysis of Wind Storage Joint Ventures Participation in Power Market Based on a Double-Layer Stochastic Optimization Model
by Bin Ma, Shiping Geng, Caixia Tan, Dongxiao Niu and Zhijin He
Processes 2019, 7(12), 896; https://0-doi-org.brum.beds.ac.uk/10.3390/pr7120896 - 02 Dec 2019
Cited by 6 | Viewed by 2162
Abstract
The volatility of a new energy output leads to bidding bias when participating in the power market competition. A pumped storage power station is an ideal method of stabilizing new energy volatility. Therefore, wind power suppliers and pumped storage power stations first form [...] Read more.
The volatility of a new energy output leads to bidding bias when participating in the power market competition. A pumped storage power station is an ideal method of stabilizing new energy volatility. Therefore, wind power suppliers and pumped storage power stations first form wind storage joint ventures to participate in power market competition. At the same time, middlemen are introduced, constructing an upper-level game model (considering power producers and wind storage joint ventures) that forms equilibrium results of bidding competition in the wholesale and power distribution markets. Based on the equilibrium result of the upper-level model, a lower model is constructed to distribute the profits from wind storage joint ventures. The profits of each wind storage joint venture, wind power supplier, and pumped storage power station are obtained by the Nash negotiation and the Shapely value method. Finally, a case study is conducted. The results show that the wind storage joint ventures can improve the economics of the system. Further, the middlemen can smooth the rapid fluctuation of power price in the distribution and wholesale market, maintaining a smooth and efficient operation of the electricity market. These findings provide information for the design of an electricity market competition mechanism and the promotion of new energy power generation. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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19 pages, 2044 KiB  
Article
Advanced Methodologies for Biomass Supply Chain Planning
by Duy Nguyen Duc and Narameth Nananukul
Processes 2019, 7(10), 659; https://0-doi-org.brum.beds.ac.uk/10.3390/pr7100659 - 26 Sep 2019
Cited by 8 | Viewed by 4049
Abstract
Renewable energy resources have received increasing attention due to environmental concerns. Biomass, one of the most important renewable energy resources, is abundant in agricultural-based countries. Typically, the biomass supply chain is large due to the huge amount of relevant data required for building [...] Read more.
Renewable energy resources have received increasing attention due to environmental concerns. Biomass, one of the most important renewable energy resources, is abundant in agricultural-based countries. Typically, the biomass supply chain is large due to the huge amount of relevant data required for building the model. As a result, using a standard optimization package to determine the solution for the biomass supply chain model might not be practical. In this study, the focus is on developing and applying advanced methodologies that can be used to determine a solution for the biomass supply chain model efficiently. The decisions related to plant selection, and distribution of biomass from suppliers to plants require optimization. The methodologies considered in this research are based on stochastic programming, parameter search, and simulation-based optimization. Computational results and managerial insights based on case studies from different regions of Vietnam are provided. The results show that parameter search is suitable for small problems only, while stochastic programming is suitable for small and medium problems. For large problem, simulation-based optimization performs better when considering the quality of the solution and the run time, although, this method does not guarantee an optimal solution. It provides good solutions where the gaps to the optimal solutions are between 0.59% and 8.41%. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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24 pages, 2095 KiB  
Article
Large-Scale Green Supplier Selection Approach under a Q-Rung Interval-Valued Orthopair Fuzzy Environment
by Limei Liu, Wenzhi Cao, Biao Shi and Ming Tang
Processes 2019, 7(9), 573; https://0-doi-org.brum.beds.ac.uk/10.3390/pr7090573 - 29 Aug 2019
Cited by 19 | Viewed by 2778
Abstract
As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee profit and sustainable development. Green supplier selection (GSS), which is a key segment of GSCM, has been investigated to put [...] Read more.
As enterprises pay more and more attention to environmental issues, the green supply chain management (GSCM) mode has been extensively utilized to guarantee profit and sustainable development. Green supplier selection (GSS), which is a key segment of GSCM, has been investigated to put forward plenty of GSS approaches. At present, enterprises prefer to construct the large-scale teams of decision makers to obtain the more reasonable ranking results during GSS process. However, the existing methods pay little attention to the large-scale GSS procedure. To investigate the GSS issue with a large-scale group of decision makers, a new GSS approach under a q-rung interval-valued orthopair fuzzy environment is developed. The q-rung interval-valued orthopair fuzzy numbers are introduced to describe the evaluation information of green suppliers. Combined with a clustering approach and several clustering principles, the large-scale decision makers are divided into several subgroups. Next, the similarity measures between the evaluation matrices are computed to determine the weights of subgroups, and the collective evaluation information can be obtained using the q-rung interval-valued orthopair fuzzy aggregation operator. According to the weighted entropy measure, the weights of criteria are calculated; then, the q-rung interval-valued orthopair fuzzy multi-objective optimization on the basis of ratio analysis plus the full multiplicative form (q-RIVOF-MULTIMOORA) method is constructed to determine the best green supplier. At last, a practical GSS example is applied to show the feasibility of the proposed approach, and the sensitivity and comparative analyses indicate that for the large-scale GSS issues, the proposed approach can obtain the more robust and reasonable ranking results. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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Review

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22 pages, 2697 KiB  
Review
Additive Manufacturing for Repair and Restoration in Remanufacturing: An Overview from Object Design and Systems Perspectives
by Rahito, D. A. Wahab and A. H. Azman
Processes 2019, 7(11), 802; https://0-doi-org.brum.beds.ac.uk/10.3390/pr7110802 - 03 Nov 2019
Cited by 84 | Viewed by 11843
Abstract
Repair and restoration is an important step in remanufacturing as it ensures end-of-life products are returned to as-new condition before entering the subsequent life cycle. Currently, such processes are carried out manually by skilled workers. The advent of additive manufacturing (AM) has encouraged [...] Read more.
Repair and restoration is an important step in remanufacturing as it ensures end-of-life products are returned to as-new condition before entering the subsequent life cycle. Currently, such processes are carried out manually by skilled workers. The advent of additive manufacturing (AM) has encouraged researchers to investigate its potential in automated repair and restoration, thus rendering it as a more effective method for remanufacturing. However, the application of this widespread technology for repair and restoration in remanufacturing is still new. This paper provides an overview of the principles and capabilities offered by the existing metal AM technology for object repair and restoration namely, direct energy deposition, powder bed fusion, and cold spray technology. Their applications in the repair and restoration of remanufacturable components are presented and discussed along with issues requiring attention from the perspectives of object design and process systems capabilities. The study provides a compilation of the challenges in AM repair and restoration, which primarily lie in the aspects of geometrical complexity, geometric dimensioning and tolerancing, material compatibility, and pre-processing requirements since it is critical for remanufacturing to restore end-of-life components to as new-condition. The paper concludes with suggestions for further works in AM restoration to enable product life cycle extension in the circular economy. Full article
(This article belongs to the Special Issue Advances in Sustainable Supply Chains)
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