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The purpose of this study is to generate a quantitative means of assessing the relationship between lean production practices and a company’s sustainable performance. A composite lean index (CLI) is formulated using multi-attribute value theory (MAVT) in order to measure a firm’s lean performance. A composite sustainability index (CSI) is developed using MAVT to measure a company’s sustainable performance considering its quadruple bottom line. Lastly, a multiple layer data envelopment analysis (MLDEA) model is set up to evaluate a company’s sustainable performance using its lean manufacturing practices. The CLI is considered as the virtual input to the MLDEA model while the (CSI) is treated as the virtual output. "Efficient" firms are determined to score high in Supplier and Customer Relationships and Human Resources whereas "inefficient" companies scored low in Supplier and Customer Relationships and Process and Equipment. Furthermore, "efficient" companies are found to exhibit high scores in Worker Training, Parts Delivered JIT by Supplier, and Customer Orders Delivered JIT while "inefficient" companies have low scores in Orderliness and Cleanliness in the Plant, Error-Proof Equipment, and Rigorous Preventive Maintenance.

Manufacturing companies worldwide are faced with the critical issue of sustainable development. The aim of this paper is to develop a quadruple bottom line-based composite sustainability index which can be used by manufacturing firms in measuring their sustainable performance. The proposed index simultaneously considers a firm's economic performance, social performance, environmental performance, and corporate governance. Field study results indicated that an index having a value from 0 to 1 can indeed be computed based on several sustainability indicators expressed in varying units. The index can be employed for performance evaluation to monitor the sustainable performance of a manufacturing company through the years. It can also be utilized for benchmarking to compare sustainable performance with other firms.

The direction of current literature in addressing sustainability issues in the manufacturing sector highlights some models and approaches that are usually based on the concept of the triple-bottom line. However, as a functional unit in a manufacturing organization, the role of the manufacturing function in creating competitiveness has been outdone by the current demands of sustainability such that integrating sustainability and competitiveness remains a significant gap. This paper proposes a unifying framework in formulating a manufacturing strategy which espouses sustainability with due consideration of the manufacturing's internal and external competitive functions. The proposed framework integrates the features based on the classical theories of manufacturing strategy and the other features that must be considered to transform a firm's manufacturing strategy into a sustainable manufacturing strategy. This framework serves as a guide for decision-makers in identifying policies in various manufacturing decision areas that would comprise a sustainable manufacturing strategy. Results of recent empirical studies that are based on the models generated from the framework are reported in this paper.

The growing industrial interest in adopting sustainability programmes has ushered in studies regarding sustainability indicators which have continually flourished in current literature. However, limited attention is given to the development of priority ranking, which is an important input for any adopting firm. This paper presents a hybrid multi-criteria approach in determining priority areas in sustainable manufacturing (SM). Using fuzzy analytic hierarchy process to address uncertainty in hierarchical decision-making, this paper determines SM priority strategies and eventually identifies even lower level strategies. The computed sustainable manufacturing index is presented at both the organizational and operational levels for a real case study of an industrial plastic manufacturing firm. This work provides a detailed and transparent hierarchical decision-making approach based on SM framework, the use of which could be valuable to practicing managers across industries in their pursuit of greater ...

Data envelopment analysis is a popular method of evaluating the performance of almost all types of organizations. The aim of this paper is to construct a twolayer DEA model which can be utilized to evaluate the sustainable performance of a manufacturing company based on its degree of leanness. The lean indices are treated as virtual inputs while the sustainability indices are considered as virtual outputs. Empirical results indicated that efficient companies scored high in Human Resources and Supplier and Customer Relationships as well as in Economic and Social Performance. This paper highlights the positive effects of adopting lean manufacturing practices on a company’s sustainable performance.

Received: 5 February 2015 Abstract Accepted: 20 March 2015 This paper adopts a probabilistic fuzzy analytic network process (PROFUZANP) approach in developing a sustainable manufacturing strategy. In this hybrid method, analytic network process handles the complexity of the problem structure under consideration, fuzzy set theory is used to describe vagueness in individual decision-making and probability theory is used to handle randomness in group decision-making. This holistic methodological approach addresses complexity and uncertainty both in individual and group decision-making which is useful in modeling group decisions such as developing a sustainable manufacturing strategy. In this work, an inclusive approach of integrating traditional manufacturing strategy concepts and sustainable manufacturing principles is proposed as a unifying decision model. The proposed decision structure adopts the hierarchical structure of manufacturing strategy and explores the presence of strategic responses and stakeholders’ interests as significant components of sustainability. Using PROFUZANP, the decision model identifies the content policies of sustainable manufacturing strategy. This content strategy is expected to address both competitiveness and sustainability of manufacturing firms. Results are reported in this paper along with insights and future work. The contribution of this work is the integration of manufacturing strategy and sustainability into a coherent decision framework that requires the use of PROFUZANP in dealing with complex and uncertain group decision-making problem.

This paper presents a decision framework that highlights the integration of manufacturing strategy (MS) and sustainability along with strategic responses as a significant component. This integration raises complexity and uncertainty in decision-making following the number of subjective components with their inherent relationships that must be brought into context and the huge amount of required information in eliciting judgments. Thus, a proposed hybrid multicriteria decision-making (MCDM) approach in the form of an integrated probabilistic fuzzy analytic network process (PROFUZANP) is adopted in this work. In this method, analytic network process (ANP) serves as the main framework in identifying policy options of manufacturing strategy. Fuzzy set theory (FST) is used to describe vagueness in decision-making which is carried out by eliciting judgments in pairwise comparisons using linguistic variables with corresponding triangular fuzzy numbers (TFNs). Probability theory is used to handle randomness in aggregating judgments of multiple decision-makers. Results show that a stakeholder-oriented approach is considered the most relevant strategic response in developing a sustainable manufacturing strategy. The contribution of this work lies in identifying the policies which constitute a sustainable manufacturing strategy using an integrated MCDM approach under uncertainty.

This paper proposes an evaluation framework of input elements in developing sustainable manufacturing (SM) initiatives using the hierarchical structure of sustainability indicators set developed by the US National Institute of Standards and Technology (US NIST) and the analytic hierarchy process (AHP). Determining priority input elements in the development process is essential to ensure that SM initiatives are responsive to the demands of sustainability at firm level. This evaluation exposes a challenge due to the multi-criteria nature of the problem and the presence of subjective criteria with limited available information on their measurement systems. The use of AHP in the context of the hierarchical structure of the US NIST sustainability indicators set provides a comprehensive and promising approach in identifying fundamental inputs in developing effective programs and initiatives that address sustainability. The contribution of this work lies on presenting a framework that could guide decision-makers, in a way that is simple and comprehensive, in their attempt to promote sustainability. Results and implications are reported in this work.

This paper presents a methodology that holistically captures the uncertainty of judgment in 'quasi-collaborative' group decision-making in the context of the analytic hierarchy/network process. The proposed method is motivated mainly by the two uncertainty approaches that seemingly diverge in literature: the simulation approach and the fuzzy set theory (FST) approach. In the proposed method, FST is used to handle the judgmental uncertainty of individual decision-maker while simulation addresses randomness and uncertainty when individual judgments are aggregated as a group decision. An illustrative problem is presented in this paper along with a numerical experiment that attempts to compare the efficacy of the proposed methodology with existing methods. Results show that the method is more capable of handling uncertain group decisions through simulation runs and it can perform sensitivity analysis which is essential in testing robustness of judgment results. Finally, the proposed method can identify non-expert member of the group.

This paper develops an approach that explores the impact of stakeholders' interests in developing a sustainable manufacturing strategy. Manufacturing firms are faced with the challenge of integrating sustainability with the classical function of manufacturing. To integrate these two objectives is to take into consideration different stakeholders' interests as significant drivers toward sustainability. This work explores the significance of these interests in developing a manufacturing strategy using the proposed probabilistic fuzzy analytic network process. The method handles the complexity of the decision framework and judgment elicitation in pairwise comparisons is described using linguistic variables with equivalent triangular fuzzy numbers. Probability theory is then used to merge the judgments of multiple decision-makers. The method is useful for handling complexity and uncertainty in group decision-making. Results show the content of the sustainable manufacturing strategy. Insights and future works are also discussed.

This paper investigates the effect of noise and the effect of a redundant impulsive auditory alarm signal on production operators' response to machine downtime in a semiconductor manufacturing system. Machine uptime is essential for productive and efficient production system and therefore downtime calls for an immediate response. Given a higher machine-to-man ratio, there is a difficulty in achieving quick response to machine downtime. For this end, ergonomic tower lamps with visual and auditory displays are used in most semiconductor manufacturing system to alert production operators and therefore minimize response time. The results of this study showed that a less noisy environment enhances operators' response to machine downtime. This proves literatures' claim on the limited capacity of human perception to achieve sharper focus on tasks when noise is present. Furthermore, the results also proved that a redundant auditory alarm signal aside from visual alarm at moderately high to high noise exposure; 85–90 dBA and >90 dBA, respectively, does not improve responses as discussed by literatures. It could be, as literatures say, that on persistent exposure to alarm signals beyond permissible noise level of 85 dBA, production operators may experience alarm fatigue phenomenon - a state of failing to hear the signals. Thus, redundant auditory alarm signals are only added costs and can further increase ambient noise which may, in effect, possibly induce health-related problems.

Purpose – The purpose of the study is to describe the characteristics of the team designs in a call centre in the United Kingdom (UK) and The Philippines (RP). As the design of teams is influenced mainly by sociotechnical system theory and lean production, these are used as landmarks in the comparison.Design/methodology/approach – The primary sources of information were recorded interviews with team members and their supervisors and observation of team operations. Outgoing personnel were also interviewed. Actual day‐to‐day operation of the teams was observed over a period of three months.Findings – The case studies exhibit the characteristics of diverse production models in service firms. The UK case study was approaching the STS model whereas the RP case study was approaching the LP model but veering more to the mass production model of service firms.Research limitations/implications – The mass production model is similar to the LP model in the following dimensions: type of coordination, workplace, leade...

This paper proposes an evaluation framework of sustainable manufacturing (SM) initiatives using the hierarchical structure of sustainability indicators set adopted by the US National Institute of Standards and Technology (US NIST) in the context of the Analytic Hierarchy Process (AHP). Evaluating SM initiatives developed by manufacturing firms is crucial for resource allocation, and ensuring that investments enhance the sustainability performance of the firm. This evaluation is a challenge because of the multi-criteria nature of the problem and the presence of subjective criteria for which little or no information on their measurement systems is available. Thus, this study is appropriate due to the following reasons: (1) US NIST provides a comprehensive evaluation model of sustainability with its four-level hierarchy that provides evidence of depth and details of sustainability evaluation, and (2) AHP has the capability to handle multi-level decision-making structure with the use of expert judgments in a pairwise comparison process. A case study of a semiconductor manufacturing firm is presented to illustrate the proposed evaluation framework. Results show that firms must strengthen their financial base through programs that improve efficiency, quality and productivity before carrying out initiatives that address the environment and the immediate community. This work presents a framework that could guide decision-makers, in a way that is simple and comprehensive in their attempt to promote sustainability. http://dx.doi.org/10.13033/ijahp.v7i1.223

This work presents a decision model that highlights the integration of manufacturing strategy and sustainability with strategic responses as a significant component. Due to the complexity and uncertainty of the decision components and elements derived from literature, a proposed hybrid MCDM approach in the form of an integrated probabilistic fuzzy analytic network process (PROFUZANP) is presented. In the proposed method, analytic network process (ANP) handles complexity of the decision model. Fuzzy set theory is used to describe vagueness in decision-making which is carried out by eliciting judgment in pairwise comparisons using linguistic variables with corresponding triangular fuzzy numbers (TFNs). Probability theory is used to handle randomness when aggregating experts' judgments. Results are reported in this paper. Insights were also discussed.