Product recovery optimization in closed-loop supply chain to improve sustainability in manufacturing

When business practices shift from a traditional open supply chain to a closed loop instead, the environmental and societal issues are efficiently integrated in business development. However, even an efficiently integrated shift introduces a number of trade-offs due to the contradictory goals that emerge from that business’s economical, environmental and social dimensions. In this paper, we propose a multi-objective mixed integer mathematical problem for a generic closed-loop supply chain (CLSC) network to rationalise how a system’s product recovery helps to improve manufacturing sustainability. The CLSC network proposed in this study consists of a hybrid manufacturing facility, warehouse, distribution centres, collection centres and a hybrid recovery facility (HRF). The proposed model determines the best location for the HRF and optimal flow of products, recovered parts and material in the network while it simultaneously maximises profit, saves activity costs, helps to decrease the harmful effects of the manufacturing process and makes a positive impact on societal development. To validate the model, a numerical illustration with the help of a case study from an electrical manufacturing industry is offered. The results authenticate the approach of the model towards the fulfilment of various environmental regulations. A sensitivity analysis, completed on demand, and the return rate also assists decision-makers to manage their decisions with a broader insight towards manufacturing sustainability.     

客户导向与竞争导向影响运营绩效作用机理研究：基于模块化视角

为了揭示生产实践在市场导向影响运营绩效中的作用,基于模块化视角研究客户导向与竞争导向影响运营绩效作用机理。204份有效样本的实证研究结果表明,客户导向与竞争导向均显著正向影响产品模块化（β=0-21/0-20）,但是对流程模块化均无显著影响;产品模块化显著正向影响流程模块化（β=046）;产品模块化对运营绩效并无显著影响,但是流程模块化显著正向影响运营绩效（β=0-29）;控制变量企业规模和运营年限对运营绩效均未表现出显著作用。结果表明,模块化可以作为企业实施市场导向战略时的一种有效生产实践用于提高运营绩效,但是产品模块化和流程模块化的影响机制存在着差异。     

Modelling product-recovery processes in closed-loop supply-chain network design

Recent changes in environmental requirements have forced manufacturing operations to face a new challenge, which is to develop green strategies to design supply chains and their processes. This study describes the specific features of green supply-chain design considering end-of-life products. We propose a mixed integer linear programming model to obtain the optimal closed-loop supply-chain (CLSC) network design, in which recovery process occurs in three different ways: material recovery, component recovery, and product recovery. An extensive analysis is supported by numerical results which inform CLSC managers about the opportunities of enhancing product returns in terms of quality and quantity. To define a better CLSC strategy to increase system profitability, the volume of product returns and corresponding quality conditions should be considered in the design of a CLSC network. The numerical study provides information for us to discuss the potential benefits of product-recovery processes and the reaction of system profitability to the changes in specific CLSC parameters.     

Beyond the trade-off and cumulative capabilities models: alternative models of operations strategy

Organisations are expected to develop sound strategies relating to their core operations capabilities of cost efficiency, quality, delivery, flexibility and innovation, to gain and maintain competitive advantage. However, there is a paucity of specific models that can be used to explain and predict how organisations combine and use these capabilities. Previous research has primarily focused on the ‘trade-off’ and the ‘cumulative capabilities’ models. In this study, data from an international sample of 1438 manufacturing plants are used to explore other models that organisations are using in addition to the two predominant models. This analysis shows that, in practice, the trade-off model is not used, but the cumulative capabilities model is used extensively. Further, our proposed new models, the ‘threshold’, ‘average’ and ‘multiple’, are prevalent in many plants. Also, a small proportion of the plants have in place the ‘uncompetitive’ model. In terms of relative effectiveness, there are no significant differences between the models with respect to several measures of operational performance. Overall, this study provides empirical evidence that there are other operations strategy models beyond the trade-off and cumulative capabilities dichotomy that organisations deploy.     

An improved compromise ranking method for evaluation of environmentally conscious manufacturing programs

An environmentally responsible or environmentally conscious manufacturing (ECM) program addresses the environmental impact of the interrelated decisions that are made at various stages of product life, from conception to design, raw ECM programs consumption, processing, delivery, use, recycling and/or disposal. The evaluation of alternative ECM programs for producing a given product is similar to many strategic initiatives and their justification methodologies. This similarity arises from the fact that there are multiple attributes that need to be considered, many of which have long term and broad implications for an organisation. Only a few decision making methods were proposed in the past for ECM program evaluation for producing a given product. There is a need for a systematic and logical scientific method or mathematical tool to guide organisations in taking a proper decision about ECM program evaluation. This paper presents a multiple attribute decision making methodology for evaluation of environmentally conscious manufacturing programs for producing a given product. The methodology is based on an improved compromise ranking method considering the ECM program selection attributes and their relative importance. The proposed ‘ECM program selection index’ helps to evaluate and rank the ECM programs for producing a given product. An example is included to illustrate the approach.     

Investing in lean manufacturing practices: an environmental and operational perspective

Lean manufacturing practices (LMPs) and corporate environmental sustainability are becoming inextricably linked. Throughout the lean and green debate, many organisations have recognised that LMPs have implications for their sustainable development and competitive positioning. Not only LMPs are complex on their own, but when perceived from an environmental sustainability perspective, the decision to implement an LMP can become even more intricate. Although general tools exist, the lack of effective decision-making tools to help in the implementation of LMPs with an environmental sustainability dimension is palpable. Thus, this study tackles the aforementioned decision problem by incorporating environmental and operational performance outcome expectations as these expectations are viewed in light of the ease of implementation of various LMPs. A novel multi-criteria decision-making (MCDM) model for evaluation of LMPs is developed in this respect. The model integrates a three-parameter interval grey number with rough set theory and the TODIM method. The model is run using empirical data from six manufacturing organisations. The findings facilitate the identification of a ‘locus of investments’ for a better selection of LMPs. The robustness of the decision support model developed is assessed through sensitivity analysis.     

The fit between environmental management systems and organisational learning orientation

With the significant increase in the adoption of environmental management systems (EMSs), it is important to evaluate whether EMSs can improve the business value for organisations that adopt them. However, less is known about whether or not EMSs lead to improved firm performance with only few studies evaluating the broad link between an organisation’s environmental strategies and its business performance. Furthermore, previous studies are inconsistent in their findings about the relationship between environmental strategies and firm performance. We attribute this inconsistency to the misfit between environmental strategies and organisational learning orientation which results in operational inefficiency within the firm. This study tries to find out the proper fit pattern between EMSs and organisational learning orientation by investigating their joint effect on firm performance. Based on survey data from 214 Chinese manufacturing companies, we found that the interactions between EMSs and four dimensions of organisational learning orientation have positive impacts on firm performance. Thus, the proper organisational learning orientation for efficiency and effective EMSs is characterised by high levels of commitment to learning, shared vision, open-mindedness and knowledge sharing.     

Aligning manufacturing flexibility with environmental uncertainty: Evidence from high-technology component manufacturers in Taiwan

While flexibility improvement is among the top concerns of manufacturing managers, managers are advised to choose the dimensions of flexibility they want in their plants. This study investigates the strategic choice of aligning flexibility development with the external environment that manufacturing managers face. Considering the nature of the high-technology industry in Taiwan, we measure environmental uncertainty based on the dimensions of customer demand, supply, competitors and product technology. Empirical data were collected from manufacturing firms in Taiwan. We then applied path analysis to examine the effect of aligning three types of flexibility: product mix, new product and volume with specific dimensions of environmental uncertainty. The results indicate that the matching of manufacturing flexibility with environmental uncertainty is necessary to ensure profit and sales performance. When faced with certain environmental stimuli, management should choose to emphasize and develop particular manufacturing flexibility.     

Measuring critical success factors of TQM implementation successfully – a systematic literature review

In times of globalisation and international trade, the concept of total quality management (TQM) as a strategy to enhance organisational performance is growing in importance. To exploit the benefits provided by TQM, organisations must manage the complex implementation process successfully. Therefore, organisations need to measure critical success factors (CSFs) when introducing TQM. However, previous research has developed a plethora of measurement instruments and researchers do not agree on certain factors or on one single measurement instrument. A systematic literature review is conducted to structure and clarify the scattered research field. The analysis of 145 studies reveals that CSFs can be classified into 11 distinct dimensions. The article proposes a three-level framework and a holistic set of measurement instruments to help researchers and managers measure each critical dimension in a timely and comprehensive manner. A focus group consisting of six quality managers validated these results. The study concludes with further findings and future research. Deficiencies of current measurements are presented and the article discusses the finding that human related factors are regarded as highly relevant but have remained low on many researchers’ and practitioners’ agendas. Hence, this article is a major contribution to structure the complex research field of measuring CSFs of TQM implementation.     

The effects of product modularity on launch speed

Extant literature suggests that product modularity positively and directly impacts the timeliness and frequency of new products as well as manufacturing performance, particularly flexibility. Little is known about the nature of these relationships, however, since few empirical studies have been done. Important questions remain unanswered including whether the effect of modularity on launch speed is direct or indirect, and what role other constructs might play. This study explores these issues by examining the effects of product modularity on launch speed within a holistic framework that considers the roles of product platforms and manufacturing flexibility. Drawing upon dynamic capabilities theory in the resource-based view, the model depicts product modularity as antecedent to product platforms, product platforms as antecedent to manufacturing flexibility and manufacturing flexibility as antecedent to launch speed. The model is strongly supported by an analysis of 93 manufacturers. Results reveal a positive effect of product modularity on launch speed, but it is delivered through the mediating effects of product platforms and manufacturing flexibility. In contrast to earlier work, the findings show modularity alone is an insufficient condition for the timely and frequent introduction of new products. Rather, launch speed is engendered by a ‘gestalt’ of dynamic capabilities.     

Information infrastructures for on-line measurement of non-productive greenhouse gas emissions in manufacturing: case of the brewing industry

A novel information infrastructure designed to measure key components of the greenhouse gas emission ‘opportunity cost’ in a production environment is proposed. The data-driven metrics facilitate drill-down to provide visibility of constituent parts. Contemporary metrics typically focus on direct energy consumption and are often normalised against units of product produced. Such metrics have proven to be useful for monitoring trends in relative performance and for benchmarking against other plants. However, they typically do not provide visibility of energy consumption (carbon emissions) that did not directly contribute to the production of saleable product. With the community's ever increasing focus on sustainability and climate change, the environmental impact of industry has come under greater scrutiny. The proposed information infrastructure provides a new level of transparency enabling stakeholders to see the portion of utilities consumption (or greenhouse gas impact) that did not directly contribute to saleable product; the non-productive greenhouse gas emission impact in a manufacturing environment. A case study is included depicting results from a pilot implementation in a packaging line in a brewery.     

Performance evaluation framework for sustainable freight transportation systems

Sustainability in freight transportation demands for a balance among economic, environmental, and social aspects in shipping commodities throughout a supply chain. The performance evaluation of sustainable freight transportation (SFT) systems is of prime importance as it facilitates perpetual and objective assessment for advancements towards sustainability targets. In this study, we propose a comprehensive framework to assess the sustainability performance of freight transportation systems. We pinpoint critical success factors (CSFs) affecting the performance of SFT by carrying out an extensive literature review and conducting a Delphi study to seek experts’ opinions from industry as well as academia. Further, a comprehensive hierarchical framework is developed to establish inter-relationships among these CSFs followed by prioritisation of these CSFs. The application of the proposed framework is illustrated through a case example. This framework would also serve as a reference for decision-makers in selecting the most sustainable freight transportation system.     

From closed-loop to sustainable supply chains: the WEEE case

The primary objective of closed-loop supply chains (CLSC) is to improve the maximum economic benefit from end-of-use products. Nevertheless, the literature within this stream of research advocates that closing the loop also helps to mitigate the undesirable environmental footprint of supply chains. Therefore, closed-loop supply chains are assumed to be sustainable supply chains almost by definition. In this paper we analyse if and when this assumption holds. We illustrate our findings based on the Electric and Electronic Equipment (EEE) supply chain. For all phases of the supply chain, i.e. manufacturing, usage, transportation and end-of-life activities, we assess the magnitude of the environmental impacts, based on a single environmental metric, namely the Cumulative Energy Demand (CED). Given the environmental hot-spots in the Electric and Electronic Equipment supply chain, we propose useful extensions for existing CLSC optimisation models to ensure that closed-loop supply chains are at the same time sustainable supply chains.     

Hierarchical environmental impact evaluation of a process in printed circuit board manufacturing

Considering the growing concerns and importance of environmental issues, manufacturing industrialists, in particular those in electronics manufacturing, are seeking methods to evaluate the environmental performance of their manufacturing processes. These environmental evaluation tools should be capable of performing detailed analysis on the environmental performance of each individual process unit, identifying the environmental improvement opportunity and providing adequate decision support to environmental engineers for process modification and operational change. This paper modifies and improves the environmental impact evaluation model already developed and provides directions for decision-making at various stages of the analysis. The decision algorithm in this revised model adopts a hierarchical environmental impact evaluation approach and uses five impact categories related to ecological health and seven categories related to human health to form the base of an evaluation hierarchy. The algorithm, with its evaluation results presented in all levels of the hierarchy, is proposed as a means of tracking, controlling and improving the environmental performance of a process. A printed circuit board case study shows the effectiveness and applicability of the algorithm. The results indicate that the electroless copper process has a higher impact on ecological health than on human health, and that the phosphoric acid in the waste components is the identified major source of the impact on ecological health.     

Social sustainable supplier evaluation and selection: a group decision-support approach

Organisational and managerial decisions are influenced by corporate sustainability pressures. Organisations need to consider economic, environmental and social sustainability dimensions in their decisions to become sustainable. Supply chain decisions play a distinct and critical role in organisational good and service outputs sustainability. Sustainable supplier selection influences the supply chain sustainability allowing many organisations to build competitive advantage. Within this context, the social sustainability dimension has received relatively minor investigation; with emphasis typically on economic and environmental sustainability. Neglecting social sustainability can have serious repercussions for organisational supply chains. This study proposes a social sustainability attribute decision framework to evaluate and select socially sustainable suppliers. A grey-based multi-criteria decision-support tool composed of the ‘best-worst method’ (BWM) and TODIM (TOmada de Decisão Interativa e Multicritério – in Portuguese ‘Interactive and Multicriteria Decision Making’) is introduced. A grey-BWM approach is used to determine social sustainability attribute weights, and a grey-TODIM method is utilised to rank suppliers. This process is completed in a group decision setting. A case study of an Iranian manufacturing company is used to exemplify the applicability and suitability of the proposed social sustainability decision framework. Managerial implications, limitations, and future research directions are introduced after the application of the model.     

A machine learning approach to optimise the usage of recycled material in a remanufacturing environment

Remanufacturing has acquired importance in recent years because of the increasing environmental concerns of manufacturing processes that deplete the Earth's resources. Some examples of remanufactured products are automobile parts, furniture, photocopiers, and computer printers. In a remanufacturing setup, raw materials are drawn from two sources: (i) ‘cores’, which are obtained from recycled products, and (ii) ‘non-recycled’ or unused materials, which are produced from minerals freshly mined from the earth. An important decision for the manager is to select material optimally from these two sources. Using cores has environmental benefits, and because they are cheap, they reduce manufacturing costs. However, their use generally increases the production time, because of the additional pre-processing usually needed, which can negatively impact service levels. When the supply of finished products is running low, to satisfy service levels, it makes sense to use unused material. This research focuses on identifying an optimal strategy of switching between the two sources of material. A reinforcement learning algorithm is used to solve the switching problem. The switching algorithm produced encouraging results, showing up to 65% cost improvements over a policy that uses only unused materials.     

The impact of lean methods and tools on the operational performance of manufacturing organisations

Evidence suggests that lean methods and tools have helped manufacturing organisations to improve their operations and processes. However, the real effect of these methods and tools on contemporary measures of operational performance, i.e. cost, speed, dependability, quality and flexibility, is still unclear. This paper investigates the impact of five essential lean methods, i.e. JIT, autonomation, kaizen, total productive maintenance (TPM) and value stream mapping (VSM), on these measures. A linear regression analysis modelled the correlation and impact of these lean practices on the operational performance of 140 manufacturing organisations around the world. In addition, structural equation modelling (SME) was used to cross verify the findings of the regression and correlation analyses. The results indicate that JIT and automation have the strongest significance on operational performance while kaizen, TPM and VSM seem to have a lesser, or even negative, effect on it. This paper provides further evidence regarding the effects that lean practices have on the performance of organisations and thus the research offers companies, and their managers, a better understanding of the relationship between the lean strategy and the performance of their operations.     

Relationship building,lean strategy and firm performance: an exploratory study in the automotive supplier industry

In contrast to previous literature, we propose that commitment to lean strategy should be preceded by building close relationships with key supply chain partners (suppliers and customers). Two aspects of lean strategy, lean manufacturing and lean design are studied in this paper. We hypothesize that relationship building positively affects both aspects of lean strategy, which in turn positively influences firm performance. To test these relationships, we use data from the top 150 auto suppliers to the ‘Big Three’ original equipment manufacturers (OEMs). The results show positive relationships between (1) relationship building and lean design, (2) relationship building and lean manufacturing, and (3) lean design and firm performance. This suggests that relationship building is more valuable for enhancing the ‘product’ aspects of lean strategy as opposed to the ‘process’ aspects of lean strategy. Process aspects of lean strategy appear to be largely a function of internal efforts.     

The impact of host country regulatory quality on the value creation process in e-business supply chains

The use of e-business (EB) applications has reshaped an organisations’ supply chain structure. EB applications have enabled supply chain organisations to integrate their upstream and downstream supply chain processes to reach higher performance outcomes. Employing the resource-based view and contingency perspective as theoretical anchors, we propose and test a model of the relationship between EB applications, supply chain integration and financial performance that is moderated by a country’s regulatory quality. Cross-country data have been collected from 637 organisations through the International Manufacturing Strategy Survey research initiative. We hypothesise that the efficacy of the EB value creation process depends on the regulatory quality of the country that companies are located in. Results indicate that EB has a stronger impact on supply chain integration and supply chain integration has a stronger impact on financial performance, if the companies are situated in countries with high quality regulatory levels.     

The impact of sales and operations planning practices on manufacturing operational performance

There is a lack of rigorous empirical studies directly examining the impact of sales and operations planning (S&OP) practices on manufacturing operational performance. This paper aims to fill this gap by analysing a sample of 725 manufacturers from 34 countries. Hypotheses relate internal S&OP, integration with suppliers (IS) and integration with customers with manufacturing operational performance (delivery, quality and flexibility). The constructs were validated with structural equation modelling and the hypotheses were tested using multiple stepwise regression. Our findings showed a positive and moderate-to-large effect of internal S&OP on manufacturing performance, controlling for firm size, country economic development and market dynamics. There was no significant impact of supply chain integration on manufacturing performance. However, we found that IS positively moderated the relationship between internal S&OP and performance, suggesting that firms with mature IS amplify the effect of internal S&OP on performance. The study is among the first to empirically and rigorously establish the impacts of S&OP practices on manufacturing performance, using a large sample of manufacturers spanning different countries, markets and firm sizes. Results show that S&OP practices have a broad impact across several performance dimensions and are a powerful lever for generating manufacturing performance.