Sustainable Manufacturing Systems Research Articles

On Predictive Maintenance in Industry 4.0: Overview, Models, and Challenges

In the era of the fourth industrial revolution, several concepts have arisen in parallel with this new revolution, such as predictive maintenance, which today plays a key role in sustainable manufacturing and production systems by introducing a digital version of machine maintenance. The data extracted from production processes have increased exponentially due to the proliferation of sensing technologies. Even if Maintenance 4.0 faces organizational, financial, or even data source and machine repair challenges, it remains a strong point for the companies that use it. Indeed, it allows for minimizing machine downtime and associated costs, maximizing the life cycle of the machine, and improving the quality and cadence of production. This approach is generally characterized by a very precise workflow, starting with project understanding and data collection and ending with the decision-making phase. This paper presents an exhaustive literature review of methods and applied tools for intelligent predictive maintenance models in Industry 4.0 by identifying and categorizing the life cycle of maintenance projects and the challenges encountered, and presents the models associated with this type of maintenance: condition-based maintenance (CBM), prognostics and health management (PHM), and remaining useful life (RUL). Finally, a novel applied industrial workflow of predictive maintenance is presented including the decision support phase wherein a recommendation for a predictive maintenance platform is presented. This platform ensures the management and fluid data communication between equipment throughout their life cycle in the context of smart maintenance.

A descriptive statistical analysis of barriers to the adoption of integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS) in Indian manufacturing industries

PurposeScarcity of resources and ever-changing demand have attracted the government and manufacturers for an integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS). Many organizations failed to adopt ISGLSAMS due to various barriers. The purpose of this paper is to identify and rank the various barriers to ISGLSAMS and to analyze the correlations among the various barriers to ISGLSAMS so that the adoption of ISGLSAMS can be implemented in manufacturing organizations for more sustainable development of the industries, and industrial ecology.Design/methodology/approachA three tiers methodology is used to analyze the barriers to the adoption of ISGLSAMS. First, a total of 24 ISGLSAMS barriers are identified through a comprehensive literature review. Then data are collected with a structured questionnaire from 108 Indian manufacturing industries. Then, the sign test is used to check the relevance and significance of barriers. Then ISGLSAMS barriers are ranked based on the median and standard deviation. Spearman's correlations between the ISGLSAMS barriers are identified and studied to strengthen the in-depth understanding of correlations among the barriers.FindingsThe result shows that most of the Indian manufacturing industries agreed with the selected barriers to the adoption of ISGLSAMS. Low supplier commitment, uncertain financial benefits, the misconception of high cost, difficulty in evaluation of system performance throughout the life cycle, complexity in ISGLSA process design, the complexity of management of ISGLSAMS, complexity in ISGLSA system design, lack of updated information, complexity in ISGLSA product design and uncertain future legislation are found the major barriers for the ISGLSAMS in Indian manufacturing industries. While lack of leadership, low top management commitment, lack of government support, organizational structure, low employees' commitment, technological risk and low public pressure are considered minor barriers for the ISGLSAMS. Inter-relationships study of the barriers further contributes to the methodology to overcome the barriers.Practical implicationsThe study contributes to a better understanding of ISGLSAMS barriers. Through this study, government, stakeholders and policymakers may plan the policy, roadmap and strategies to overcome the barriers to the ISGLSAMS. This will lead to the successful adoption of ISGLSAMS for more sustainable development of manufacturing industries in India.Originality/valueThis work contributes to identifying the barriers to a more sustainable manufacturing system, i.e. ISGLSAMS (7Rs based), and prioritizing them in Indian manufacturing industries. The research also contributes to the (1) study of inter-relationships among the ISGLSAMS barriers for analyzing the effect of one barrier over another barrier, and (2) ISGLSAMS literature because the sustainable manufacturing literature still lags the achievement of sustainability goals due to 6Rs focus.

Adaptive Cognitive Manufacturing System (ACMS) – a new paradigm

Innovation and transformative changes in products, manufacturing technologies, business strategies, and manufacturing paradigms have profoundly changed the manufacturing systems. In addition to being environmentally, economically socially sustainable, manufacturing systems are increasingly using intelligent technologies to be even more resilient, responsive, and adaptable. A new Adaptive Cognitive Manufacturing Systems (ACMS) paradigm, its drivers, enablers, and characteristics, including cognitive adaptation, is presented. Classification and definitions of four types of adaptability in manufacturing systems are included. Human-centric collaboration of workers and intelligent machines and applications, and the future of work in cognitive adaptive manufacturing systems are outlined. Cognitive Digital Twins (CDT), their features, evolution, and their use to support humans in intelligent, collaborative manufacturing settings are discussed. Industrial applications and case studies are used to illustrate the presented concepts and paradigms. Challenges and future research directions to achieve the ACMS paradigm and implement more intelligent, more adaptive, and sustainable manufacturing systems are presented. The presented novel concepts and technologies make significant contributions to the fast-evolving field of manufacturing systems. This pioneering research sheds light on many important future research topics and provides a road map and motivation for researchers in this field.

Energy consumption control in the two-machine Bernoulli serial production line with setup and idleness

In recent years, the topic of sustainable manufacturing system design with energy saving features has received increasing attention. For a typical production line setting, the machines are subject to random breakdown and restart besides blockage and starvation, and they are usually connected via buffer areas with finite capacity. In the present study, the energy consumption of the serial production line with two Bernoulli machines is considered, with an aim to minimise the total energy consumption under a desired production rate. The energy consumption of the two-machine system is composed of the energy needed to setup, to remain idle, and for actual manufacturing. In order to minimise the total energy expenditure, a nonlinear fractional polynomial optimisation model is constructed, which is first converted to a nonlinear polynomial optimisation problem. Then the property of the total energy cost is analysed via the sum of squares (SOS) method. To speed up the solving process, a new heuristic approach named energy consumption saving (ECS) algorithm is proposed considering the monotonicity and local optimality of the energy cost function. Finally, by presenting optimal configurations of the production line with different throughputs, buffer capacities, and energy parameters, a simulation-based study is performed to validate the SOS and ECS algorithms.

An analysis of drivers for the adoption of integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS) in Indian manufacturing industries

PurposeScarcity of resources and ever-changing customer demand has driven the manufacturing organization to opt for an integrated sustainable-green-lean-six sigma-agile manufacturing system (ISGLSAMS). The purpose of this study is to identify and rank the various drivers for the adoption of ISGLSAMS for the more sustainable development of the industries.Design/methodology/approachUsing a survey questionnaire, data were collected for the 14 ISGLSAMS drivers, identified through the literature review, from 108 Indian manufacturing industries. The sign test is used to check the relevance and significance of drivers. ISGLSAMS drivers are ranked based on the median and standard deviation. A multiple regression model was employed to investigate the effects of other drivers on the highest-ranked driver to strengthen the understanding of the drivers.FindingsCompetition, customer demand, technological changes, supply chain pressure, cost benefits, incentives, top management commitment and future legislation are found the strongest drivers for ISGLSAMS. For administering the competition for ISGLSAMS policymakers must focus on the availability of organization resources, customer demand, future legislation, incentives, supply chain pressure and technological developments.Practical implicationsThe study contributes to a better understanding of ISGLSAMS drivers. Through this study government, stakeholders and policymakers may plan the policy, roadmap and strategies to drive the manufacturing organizations for the adoption of ISGLSAMS for more sustainable development of industries in India.Originality/valueThis work contributes to the identification and prioritization of the drivers for the more sustainable manufacturing system, i.e. ISGLSAMS (7 Rs based, i.e. 6 Rs of sustainability with 7th R, reconfiguration). The research also contributes to the (1) ISGLSAMS literature (2) the awareness and demand of (a) ISGLSAMS (b) reconfigurable, sustainable and modular products (c) redesign, recovery and refurbishing of the product to increase the product life cycle.

Drivers for the adoption of integrated sustainable green lean six sigma agile manufacturing system (ISGLSAMS) and research directions

Due to the scarcity of resources, and the need for preserving the resources for the future generation, there has been significant growth in research and development in a sustainable market-focused manufacturing system, in particular with the view of product recovery, waste elimination, and landfill legislation. It has extended the responsibility of manufacturing organizations to include the recovery and safe disposal of their product, process, and supply chain waste, as well as, the adoption of a sustainable quick response manufacturing system, to produce sustainable customized products. A more compatible manufacturing system and strategy are required to meet these business goals. It is observed through literature that an integrated sustainable green lean six sigma agile manufacturing system (ISGLSAMS) provides a strong platform to meet all these business, societal and ecological needs under a single umbrella. However, many organizations opt for this strategy voluntarily and many do not. It is observed through a literature survey that through this strategy organizations improve their financial, market, social, environmental, operational, and sustainable performance. The main objective of this review is to identify the various drivers for the adoption of an ISGLSAMS, so that governments, stakeholders, and policymakers may plan the strategy for motivating the organizations for the ISGLSAMS. The review also discusses the key enablers and characteristics of ISGLSAMS, product, and strategy. The review also highlights the key characteristics, and clauses of each driver, and research areas for the drivers for the adoption of ISGLSAMS. The review also shows a performance measurement or performance benchmark framework for ISGLSAMS.

An innovative approach for resource sharing and scheduling in a sustainable distributed manufacturing system

Secure, transparent, and sustainable distributed manufacturing system (DMS) is a pressing need for current Industry 4.0. In this paper, exchange of highly sensitive information in a more transparent and secure way and to avoid the misunderstandings and trust issues between the enterprises a smart contractbased on blockchain technology has been proposed in case of a distributed manufacturingenvironment. Here, we used a public-permission less Ethereum platform to execute the smart contracts in the Blockchain to process the customer orders and to identify the right enterprise. Later, a multi-objective mixed-integer linear programming (MILP) model is formulated for optimal resource sharing and scheduling in a considered sustainable DMS. The objectives of the proposed model consist of simultaneously improvement of the performance measures such as makespan, machine utilization, energy consumption, and reliability. To solve this MILP model, a new Multi-objective-based Hybridized Moth Flame Evolutionary Optimization Algorithm (HMFEO) is developed and then the effectiveness of the proposed algorithm is validated with the Non-dominated Sorting Genetic Algorithm (NSGA-III). The results obtained from implementing the model using experimental data along with different cases show the efficiency and the validity of the proposed model and solution approach. Moreover, several performance indicators like hyper volume are increased by nearly 15–20 % that shows the superiority of the proposed algorithm with the NSGA-III.

Process and production planning for sustainable reconfigurable manufacturing systems (SRMSs): multi-objective exact and heuristic-based approaches

Process and production planning for sustainable reconfigurable manufacturing systems (SRMSs): multi-objective exact and heuristic-based approaches

Product outsourcing policy for a sustainable flexible manufacturing system with reworking and green investment.

Production of defective products is a very general phenomenon. But backorder and shortages occur due to this defective product, and it hampers the manufacturer's reputation along with customer satisfaction. That is why, these outsourced products supply, a portion of required products for in-line production. This study develops a flexible production model that reworks repairable defective products and outsources products to prevent backlogging. A percentage of total in-line production is defective products, which is random, and those defective products are repairable. A green investment helps the reworking process, which has a direct impact on the market demand for products. A classical optimization solves the profit maximization model, and a numerical method proves the global optimal solutions. Sensitivity analysis, managerial insights, and discussions provide the highlights and decision-making strategies for the applicability of this model.

Sustainable manufacturing system applying on eco-design products

In this research intends to investigate the usage of two environmentally friendly design improvement methodologies to get better results in the production and user phases. During the design phase, raw material selection, manufacturing procedures, and environmental repercussions such as global warming, greenhouse gas emissions, and energy usage were all addressed. Eco-design concepts are integrated throughout the product's life cycle by using current and planned designs. The study's other goal is to consider numerous outputs from the product development process as well as sustainability practices in relation to environmental improvement in the present and future. These designs contribute to environmental preservation by drastically lowering pollution. Products that are environmentally friendly might be manufactured from scratch recycled materials.

New digital triad (DT-II) concept for lifecycle information integration of sustainable manufacturing systems

A system paradigm is a typical pattern or model of enterprise architectures (EAs) that describes constitutive system elements and their relations in achieving missions and goals of enterprises. A well-defined system paradigm and EA help enterprises in adopting appropriate manufacturing resources and technologies, optimizing plans, schedules, and controls of production lines, and coping with complexity, changes, and uncertainties of business processes cost-effectively. It is understandable that a system paradigm should be evolved along with the availability and advancement of advanced manufacturing technologies; on the other hand, new system paradigms are mostly inspired by some successful manufacturing applications of new information technologies (ITs). One of the recently developed system paradigms is Digital Manufacturing (DM) where Digital Twin (DT-I) is used to describe the interactions of virtual and physical entities. This paper discusses the concepts of DM and DT-I and rationalizes the relations of DM and DT-I; in particular, the origin and evolution of DT-I are explored in details to identify its limitations to be used as an EA for DM. It is our finding that existing IT concepts show their limitations in supporting smooth transitions when systems have to be reconfigured in dealing with long-term changes in Sustainable Manufacturing, and this is evidenced by the fact of the trend of the shortened lifespans of modern enterprises even with the aids of rapidly developed digital technologies in decades. To overcome these limitations, a new concept so called Digital Triad (DT-II) is coined and the Internet of Digital Triad Things (IoDTT) is proposed as an information integration (II) solution for digital manufacturing enterprises, and their application is illustrated through a reconfigurable robotic system example. The rationales and significances of DT-II and IoDTT as well as future research directions of DM are summarized as a conclusion.

A sustainable smart multi-type biofuel manufacturing with the optimum energy utilization under flexible production

Biofuel manufacturing from renewable biomass through a smart manufacturing system is an important alternative to fossil fuels, which helps to decrease dependability on conventional fuel and decrease carbon emanations. By utilizing efficient labors, smart machines, and minimized energy utilization, the conventional biofuel manufacturing framework can be converted into a smart sustainable manufacturing framework. The existing conventional fuel demand can be replaced by biofuel. This study efforts to make pure biofuel with less amount of carbon emanations and energy utilization through a smart multi-type biofuel manufacturing framework, where the demand of the biofuel is selling price dependent. The different energy costs including air handling cost, lighting cost are calculated in this work-in-process inventory. The carbon emissions cost is included in every stage of this model. A variable demand has introduced for the maximization of profit. To reduce energy consumption and carbon emissions, a two-stage inspection cost with a variable manufacturing rate is taken to make the manufacturing process flexible such that the amount of impure biofuel is minimized. Although a random manufacturing rate is applied through a smart manufacturing system, still impure biofuel is manufactured. The impure biofuel is remanufactured again through refining just after the well-planned manufacturing ends. In this model, the multi-delivery technique is used such that a fixed amount of biofuel of n segments of the pure biofuel is transported to market places at predetermined intervals at the time of delivery frame. The classical optimization technique is used for continuous and differentiable variables and the mixed integer programming technique is utilized for discrete variables to maximize the total profit globally. To validate the model’s usefulness, four numerical observations are studied. It is shown that by utilizing the said procedure, the percentage of impure biofuel can be decreased truly through the minimized energy consumption. The graphical representation and the sensitivity experiment show the impact of every parameter with the whole cost of the research paper. Numerical results assist to get the maximum profit and the optimum selling price of biofuel globally in a sustainable smart multi-type biofuel manufacturing system.

Process Planning, Scheduling, and Layout Optimization for Multi-Unit Mass-Customized Products in Sustainable Reconfigurable Manufacturing System

Currently, manufacturers seek to provide customized and sustainable products, requiring flexible manufacturing systems and advanced production management to cope with customization complexity and improve environmental performance. The reconfigurable manufacturing system (RMS) is expected to provide cost-effective customization in high responsiveness. However, reconfiguration optimization to produce sustainable mass-customized products in RMS is a complex problem requiring multi-criteria decision making. It is related to three problems, process planning, scheduling, and layout optimization, which should be integrated to optimize the RMS performance. This paper aims at integrating the above three problems and developing an effective approach to solving them concurrently. It formulates a multi-objective mathematical model simultaneously optimizing process planning, job-shop scheduling, and open-field layout problem to improve RMS sustainability. The penalty for product tardiness, the total manufacturing cost, the hazardous waste, and the greenhouse gases emissions are minimized. Economic and environmental indicators are defined to modify the Pareto efficiency when searching the Pareto-optimal solutions. Exact Pareto-optimal solutions are obtained by brute-force search and compared with those of the non-environmental indicator model. NSGA-III is adopted to obtain the approximate Pareto-optimal solutions in high effectiveness and efficiency. A small numerical example is applied to validate the mathematical model and resolution methods.

Strategies for assessment and implementation of sustainable manufacturing

Manufacturing has been acknowledged for the intensive use of renewable raw materials, energy sources, and a significant contributor to pollutants causing multiple environmental issues and health hazards to the community. Sustainable manufacturing is a necessary prerequisite to conserve natural resources, mitigate the adverse impacts on environment, global economy, and society. It is important to identify and understand the implementation steps and the evaluation process for developing a sustainable manufacturing system. In this review, sustainable manufacturing has been described for better understanding of the concept. The insights about existing sustainability metrics with the inclusion of environmental, economic and social aspects of sustainability has been explored. The various sustainability indicators have been documented to provide an overview for sustainability assessment framework. In addition, the gaps in the existing sustainability metrics have been identified and the future goals for tailoring the current indicators has been explored. Thus, the study provides strategies for suitable sustainability assessment and action-plan for implementation of sustainable manufacturing.

Sustainable Lean Six Sigma Competitive Manufacturing Strategy for Luggage Manufacturer

International market activities from certification bodies based on customers’ request and government policies mandate companies to focus on achieving the right economic goals by paying attention to the social welfare and providing environmentally friendly businesses. Luggage bag companies with plastic raw materials need to increase production efficiency and enhance the quality of goods. The sustainable lean six sigma competitive manufacturing strategy for luggage manufacturer is a driving force for top management of manufacturing companies to apply the operational business concept for product sustainability. Therefore, this research integrated the lean six sigma method with the sustainability concept to validate the strategy for luggage manufactures. This is a case study of a luggage company, carried out by integrating lean and quality management methods in a sustainable manufacturing system to improve the public's assessment. The purpose of this research is to create a framework by integrating the lean six sigma method and applying the sustainable paradigm to the luggage company, to help the company's efforts to meet the requirements of external stakeholders to implement a sustainable production process and solve company problems on efficiency and quality in the production process. The results of this research are to increase production efficiency and improve quality by implementing a lean six sigma competitive manufacturing strategy for luggage companies with sustainable business processes to fulfill the demands from external stakeholders.

Preface

3rd International Conference on “Computational and Experimental Methods in Mechanical Engineering” (ICCEMME-2021) 11th – 13th February, 2021 G. L. Bajaj Institute of Technology and Management, Greater Noida, India The 3rd International Conference on “Computational and Experimental Methods in Mechanical Engineering” (ICCEMME-2021) was held in Greater Noida, Uttar Pradesh, India from 11th to 13th February, 2021. This conference was organized by the Department of Mechanical Engineering at G L Bajaj Institute of Technology and Management, Greater Noida. The conference provided opportunity for academicians, researchers, students and scientists working in various domains of engineering and science such as Artificial Intelligence, Machine learning, Design, Materials, Energy, Industrial & Production Engineering, Sustainable Manufacturing Systems, Rapid Prototyping, Manufacturing Process Optimization, Machining, and Machine Tools, Computer-Aided Engineering, Manufacturing, Automation and Metrology, Industrial, Physics, Chemistry, Math’s, Management and Marketing etc.Initially, this conference was scheduled to be organized from 4th to 6th November 2020. But amid tough times of COVID-19, this conference was rescheduled to be organized from 11th to 13th February, 2021. Further, the cases of COVID-19 kept on increasing and the restrictions on travelling were imposed at local and international level. Such a situation compelled us to organize the conference in online mode. The organizing committee of ICCEMME-2021 is proud to organize the conference successfully in online mode.The inaugural and valedictory sessions were telecasted LIVE on YouTube with the help of a local broadcaster. The link for the inaugural session is https://youtu.be/I6Jcjecx4Kc Prof. S. K. Garg (DTU, Delhi) and Prof. L. M. Das (IIT Delhi) addressed the audience in the inaugural session. Prof. Prem Vrat and Prof. Kripa Shanker shared their thoughts in the valedictory session. The link for valedictory session is https://youtu.be/4fz3QwUStw8 The committee decided to opt for Google meetings for conduction of technical sessions as it has been a popular platform for virtual meetings. Each presenter was given 15 minutes for presentations (10 minutes for presentation and 5 minutes for question-answers).More than 900 papers from various domains of mechanical engineering were submitted by authors from different parts of the world. After the peer-review process 400 papers were accepted in our Conference. The editorial board of ICCEMME-2021 consisted of Prof. (Dr.) Rajeev Agrawal, Dr. Sunil Kumar Rajput, Dr. S.S Chauhan, Mr. Sandeep Chauhan and Mr. Rohit Sahu. We are very grateful to all the reviewers, both local and international, for giving their precious time and sincere effort in maintaining the quality of the papers. Their sincere feedback to the authors is highly appreciated. We extend our special thanks to Proceeding’s publication partner, Prof. Reyes Velázquez and its whole team for their continuous and constant support.The organizing committee of ICCEMME-2021 is thankful to all the sponsors for their financial support. The organizing committee is also thankful to the Management of G. L. Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, India, for their constant support. Last but not least, we are also thankful to each and every individual who contributed for making this event successful.Organizing Committee are available in the pdf

Sustainable reconfigurable manufacturing system design using adapted multi-objective evolutionary-based approaches

Nowadays, manufacturing systems should be cost-effective and environmentally harmless to cope with various challenges in today’s competitive markets. This paper aims to solve an environmental-oriented multi-objective reconfigurable manufacturing system design (i.e., sustainable reconfigurable machines and tools selection) in the case of a single-unit process plan generation. A non-linear multi-objective integer program (NL-MOIP) is presented first, where four objectives are minimized respectively, the total production cost, the total production time, the amount of the greenhouse gases emitted by machines, and the hazardous liquid wastes. Second, to solve the problem, we propose four adapted versions of evolutionary approaches, namely two versions of the well-known non-dominated sorting genetic algorithm (NSGA-II and NSGA-III), weighted genetic algorithms (WGA), and random weighted genetic algorithms (RWGA). To show the efficiency of the four approaches, several instances of the problem are experimented, and the obtained results are analyzed using three metrics respectively hypervolume, spacing metric, and cardinality of the mixed Pareto fronts. Moreover, the influences of the probabilities of genetic operators (crossover and mutation) on the convergence of the adapted NSGA-III are analyzed. Finally, the TOPSIS method is used to help the decision-maker ranking and select the best process plans.

Modelling and an improved NSGA-II algorithm for sustainable manufacturing systems with energy conservation under environmental uncertainties: a case study

ABSTRACT This study addresses a flexible job shop scheduling problem considering the energy tax regulations. We introduce two strategies as reactive scheduling to deal with two different kinds of uncertainty. The first uncertainty is about the start and processing times of the jobs with a known probability distribution. The second kind is related to machine breakdowns, modification or cancellation of the orders, and receive new orders without any known probability distribution. Two conflict objective functions are considered as minimising tax cost on surplus energy consumption and minimising total cost of jobs lateness based on soft time-windows. A bi-objective mathematical model is developed to formulate the problem. Since the problem is well-known strongly NP-hard, a new solution approach is introduced based on the NSGA-II algorithm to solve the problem in a reasonable computational time. Some test problems based on a real case study are used to evaluate the performance of the proposed solution approach. The result analysis confirms the effectiveness of the proposed algorithm and its superiority comparing with another algorithm based on the classic NSGA-II. Moreover, sensitivity analysis is done on the main parameters to provide proper managerial suggestions based on the obtained Pareto front solutions.

Energy-efficient buffer allocation problem in unreliable production lines

The buffer allocation problem (BAP) is one of the major optimization problems considered by production systems designers. The BAP is widely studied in the literature, since buffers have a great impact on improving the efficiency of production systems especially for mass production. Nevertheless, with all upcoming changes in world’s economy, industrial requirements and ecological awareness, the necessity of considering energy efficiency in manufacturing systems design becomes crucial. This paper introduces the first variant of energy-efficient buffer allocation problem (EE-BAP). It addresses a novel integrated analytical method to find the best buffer allocation that optimizes both throughput and energy consumption for serial production lines with unreliable machines. A large experimental study, based on different instances well established in the literature, is carried out to analyze the relevance of the proposed method. The obtained results show that considerable energy savings with low or almost no productivity loss are allowed. The energy-efficient BAP is a novel problem that considers the complex trade-off between throughput and energy efficiency performance and introduces new perspectives of research in the field of sustainable manufacturing systems design.

Strategic assessment and mitigation of risks in sustainable manufacturing systems

In this paper, different risk issue related in sustainable manufacturing system has been studied for performance measurement. Risks such as supply risks, operational risks, disruption risk, transportation risk, financial risks and demanad risks are identified through literature and considered for the analysis. The main objective of this paper is to quantify the impact of risks in sustainable manufacturing system using Graph Theoretic Approach (GTA) and to suggest some risk mitigation techniques .