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Sustainable manufacturing is gaining prominence in light of the rising environmental and social concerns worldwide. One major task to enhance manufacturing sustainability is assessment of the current state of sustainability of a manufacturing firm. This paper reviews the existing sustainability assessment approaches applicable for manufacturing firms and observes that most of these approaches are not easy to apply for reasons such as high amount of skill, data and time requirement. Towards bridging this gap, this study proposes a sustainability assessment approach.

The assessment approach proposed in the paper uses a predefined list of potential sustainable manufacturing practices (SMPs) covering the primary and support activity domains of a manufacturing firm's value chain. It proposes a method to assess the extent of implementation of SMPs and identify associated drivers and barriers for each SMP area/category along the value chain of a firm as well as at overall firm level. A case study from textile industry is presented to demonstrate the utility of this approach.

The sustainability assessment approach adopted in this study uses less time and skills as well as ensures comprehensive coverage of SMPs. It provided valuable information to the management of the case company on how sustainable their practices are and why?

The study highlights the importance of sustainability assessment at SMP area/category level as well as explores practice area/category specific drivers and barriers. It provides a useful approach for a quick assessment of the current state of sustainability in manufacturing firms.

This paper aims to propose a collaborative approach model developed based on observations of two aerospace manufacturing small and medium-sized enterprises (SMEs) pursuing their digital transformation toward Industry 4.0.

This research focuses on two manufacturing SMEs in North America, and data were collected using longitudinal case study and research intervention method. Data collection was performed through observation and intervention within the collaborative projects over 18 months.

A model of a collaborative approach to digital transformation (CADT) for manufacturing SMEs was produced. Based on the study findings, the collaboration manifests itself at various stages of the transformation projects, such as the business needs alignment, project portfolio creation, technology solution selection and post-mortem phase.

Research using the case study method has a limitation in the generalization of the model. The CADT model generated in this study might be specific to the aerospace manufacturing industry and collaboration patterns between manufacturing SMEs. The results could vary in different contexts.

The proposed CADT model is particularly relevant for manufacturing SMEs' managers and consultants working on digital transformation projects. By adopting this approach, they could better plan and guide their collaboration approach during their Industry 4.0 transformation.

This research provides a new perspective to digital transformation approaches in the aerospace industry. It can be integrated into other research findings to formulate a more integrated and comprehensive CADT model in industries where SMEs are significant players.

The purpose of this paper is to develop a model for sustainable manufacturing by adopting a combined approach using AHP, fuzzy TOPSIS and fuzzy EDAS methods. The proposed model aims to identify and prioritize the sustainable factors and technical requirements that help in improving the sustainability of manufacturing processes.

The proposed approach integrates both AHP, Fuzzy EDAS and Fuzzy TOPSIS. AHP method is used to generate the weights of the sustainable factors. Fuzzy EDAS and Fuzzy TOPSIS are applied to rank and determine the application priority of a set of improvement approaches. The ranks carried out from each MCDM approach is assessed by computing the spearman's correlation coefficient.

The results reveal the proposed model is efficient in sustainable factors and the technical requirements prioritizing. In addition, the results carried out from this study indicate the high efficiency of AHP, Fuzzy EDAS and Fuzzy TOPSIS in decision making. Besides, the results indicate that the model provides a useable methodology for managers' staff to select the desirable sustainable factors and technical requirements for sustainable manufacturing.

The main limitation of this paper is that the proposed approach investigates an average number of factors and technical requirements.

This paper investigates an integrated MCDM approach for sustainable factors and technical requirements prioritization. In addition, the presented work pointed out that AHP, Fuzzy EDAS and Fuzzy TOPSIS approach can manipulate several conflict attributes in a sustainable manufacturing context.

The desirability of transferring manufacturing logic and practices to service operations, strongly advocated by Levitt (1972; 1976) in two classic Harvard Business Review articles two decades ago, is now commonly challenged by both service researchers and practitioners. We defend a “production‐line approach to service” by arguing that services can “reindustrialize” by applying revised, progressive manufacturing technologies. We describe how services businesses such as Taco Bell, Southwest Airlines, and Shouldice Hospital have mastered what we call “lean” service ‐ the application of lean manufacturing principles to their own service operations. Overall, services tend to be innovation laggards, compared to manufacturing. Looking ahead, mass customization can be viewed as the convergence of service and manufacturing logic.

The purpose of this paper is to provide sector-specific empirical evidence on the comparative evaluation of total productive maintenance (TPM) and total quality management (TQM) approaches, implemented exclusively and collectively on improving manufacturing business performance.

This paper develops a multi-sector analysis framework to comparatively assess the synergistic and standalone effect of TPM and TQM improvement approaches. A total of 231 manufacturing organizations from food and beverages, textiles and electrical and electronics sectors have been extensively surveyed. These firms were further clustered into TPM focus, TQM focus and integrated TPM×TQM on the basis of their primary manufacturing strategy. Comparative assessment of these three manufacturing approaches has been evaluated using t-test statistics.

This paper highlights that adoption of integrated TPM×TQM approach is beneficial for food and beverages and electrical and electronics sectors. However, this supposition is rejected for firms operating in the textile sector.

The findings of this research are still exploratory. Future research using countrywide and cross-country approach can be undertaken to statistically generalize the findings of the present research. In-depth case studies are needed to further validate the findings of the study empirically.

The result of this study help managers and practitioners to make manufacturing strategic decision based on the nature of their operating business sector regarding adoption of TPM and TQM practices, which will further revive their firm’s competitiveness.

Every operating sector embraces a diversity of manufacturing activities based upon their competing priorities. This paper makes an attempt to present a multi-sectoral evaluation of joint implementation and effect of manufacturing programs.

The purpose of this paper is to establish a tolerance optimization method based on manufacturing difficulty computation using the genetic algorithm (GA) method. This proposal is among the authors’ perspectives of accomplished previous research work to cooperative optimal tolerance allocation approach for concurrent engineering area.

This study introduces the proposed GA modeling. The objective function of the proposed GA is to minimize total cost constrained by the equation of functional requirements tolerances considering difficulty coefficients. The manufacturing difficulty computation is based on tools for the study and analysis of reliability of the design or the process, as the failure mode, effects and criticality analysis (FMECA) and Ishikawa diagram.

The proposed approach, based on difficulty coefficient computation and GA optimization method [genetic algorithm optimization using difficulty coefficient computation (GADCC)], has been applied to mechanical assembly taken from the literature and compared to previous methods regarding tolerance values and computed total cost. The total cost is the summation of manufacturing cost and quality loss. The proposed approach is economic and efficient that leads to facilitate the manufacturing of difficult dimensions by increasing their tolerances and reducing the rate of defect parts of the assembly.

The originality of this new optimal tolerance allocation method is to make a marriage between GA and manufacturing difficulty. The computation of part dimensions difficulty is based on incorporating FMECA tool and Ishikawa diagram This comparative study highlights the benefits of the proposed GADCC optimization method. The results lead to obtain optimal tolerances that minimize the total cost and respect the functional, quality and manufacturing requirements.

The purpose of this study is to identify, evaluate and develop a structured model to measure the interrelation between critical failure factors (CFFs) that affects the implementation of the sustainable Lean Six Sigma (SLSS) framework in a manufacturing organization. Further solution approaches have been provided that inhibit those CFFs and help in successful implementation of the framework.

To find the interrelation among the selected CFFs and develop a systematic structured model, a total interpretive structural modeling (TISM) approach has been used. A 13-level model for selected CFFs has been formed after the application of the TISM approach. Further classification of CFFs has been performed for a better understanding of their nature through MICMAC analysis.

A total of 26 SLSS CFFs have been identified through a detailed study of case organization, various literature reviews and experience of panel experts toward developing a systematic model of CFFs. The solution approach has been provided by panel experts based on their industrial experiences after observing the role of CFFs in the developed model. Based on the analysis, it was found that most dependent and dominant CFFs affect the implementation of the SLSS framework in the case organization.

This study helps SLSS practitioners, project managers, decision-makers and academicians of manufacturing industries to a better understanding of the failure factors and their interrelations while implementing the SLSS framework in manufacturing organizations. This study also guides the systematic solution approach which helps in tackling such problems that occurred in manufacturing organizations.

In this study, the TISM-based structural model of CFFs for implementing the SLSS framework in manufacturing organizations has been proposed which is a very new effort in the area of a manufacturing environment.

This paper aims to investigate an integrated approach that aims at enhancing the application process of value stream mapping (VSM) method. It also proposes an extended VSM called Economic and Environmental VSM(E-EVSM). The proposed approach highlights the improvement of economic and environmental performances.

The proposed approach has studied the integration of VSM, fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy quality function deployment (QFD) to improve the economic and environmental performances of manufacturing processes. The VSM method is used for data collection and manufacturing process assessment, whereas fuzzy DEMATEL is used to analyse the current state map. Finally, fuzzy QFD is used to organize the improvement phase of VSM method.

The clear findings of this research prove the effectiveness of VSM method on the environmental and economic performances of manufacturing processes. In addition, the proposed approach will show the advantages of fuzzy DEMATEL and fuzzy QFD approaches in improving the application of the VSM method.

The limitation of this study includes the lack of consideration of other dimensions such as social, technological and managerial. In addition, the proposed approach studied an average set of environmental and economic indicators.

The novelty of the proposed approach is proved by the development of an extended VSM method (E-EVSM). Also, the proposed approach contributes by a new methodology for analysing and improving the current state map of manufacturing processes.

This paper recommends a method entitled “SMED 4.0” as a development of conventional single minute exchange of die (SMED) to avoid defect occurrence during production and improve sustainability, besides reducing setup time.

The method builds upon an extensive literature review and in-depth explorative research in SMED and zero defect manufacturing (ZDM). SMED 4.0 incorporates an evolutionary stage that employs predict-prevent strategies using Industry 4.0 technologies including the Internet of Things (IoT) and machine learning (ML) algorithms.

It presents the applicability of the proposed approach in (1) identifying the triple bottom line (TBL) criteria, which are affected by defects; (2) predicting the time of defect occurrence if any; (3) preventing defective products by performing online setting on machines during production as needed; (4) maintaining the desired quality of the product during the production and (5) improving TBL sustainability in manufacturing processes.

The extended view of SMED 4.0 in this research, as well as its analytical approach, helps practitioners develop their SMED approaches in a more holistic way. The practical application of SMED 4.0 is illustrated by implementing it in a real-life manufacturing case.

Today, manufacturing companies are facing a fierce competition and are under great pressure to cut costs for survival in the market. So emphasis is given to enhance quality, minimize waste, customer delight and increasing productivity through reduction in wastage of resources. But, most companies hesitate to implement all measures simultaneously to acquire lean manufacturing because of some practical/ capital constraints. Therefore, the purpose of this paper is to develop a phase-wise approach to implement lean manufacturing.

The paper opted for an exploratory study using the qualitative flexible system methodology framework proposed by Sushil (1994) and options field methodology proposed by Warfield (1982, 1990) including rigorous group discussion comprising the employees representing middle and senior management with productivity improvement backgrounds. The response of experts was recorded using a specially designed instrument in the light of the parameters suggested in group discussion. The measures/ actions were arranged in the decreasing order of their cumulative score.

The paper provides a phase-wise approach to implement lean manufacturing. Mixed approach is preferred over the other three approaches to implement lean manufacturing. Thirty measures/actions contributing to mixed approach are identified to implement lean manufacturing in three phases. A three-phase approach is developed: 10, 14 and six measures in the first, second and third phases, respectively, are identified to implement lean manufacturing after considering the practical constraints faced by the companies.

All the measures/actions suggested to implement lean manufacturing are focused on the engineering manufacturing industry. Thus, the research results may lack generalizability and are limited to engineering manufacturing industry. The model developed in this research is based upon experts’ opinions. The experts’ opinion may be biased. The results of the model may vary in the real-world setting.

The present paper provides guidelines to practitioners for implementing lean manufacturing in phases. Hopefully, this study will motivate the firm’s management for implementing lean manufacturing and limiting the effect of practical constraints and scarcity of resources.

This paper fulfills and identifies the need to develop an approach to implement lean manufacturing phase wise because of practical constraints.