Sustainable Manufacturing Strategies Research Articles

Tracking the Biological Incorporation of Exogenous Molecules into Cellulose Fibers with Non‐Radioactive Iodinated Glucose

AbstractSemi‐synthetic biological fabrication explores biological systems and their biosynthetic pathways as inspiration for designing precursor analogs that can be metabolized in a similar manner as the natural substrates by organisms to yield new materials with tailored properties. Here we report the biological incorporation of a metabolizing iodinated glucose analog (2‐Deoxy‐2‐iodo‐D‐glucose, DIG) into Gossypium hirsutum cotton fibers in an ovule in‐vitro model. Structural modifications occur at the level of crystallite arrangement and compaction, with amorphization of the fibers and alteration of the H‐bond network between the cellulose nanofibrils. We further show that DIG can serve as a non‐radioactive micro computed tomography contrast agent (μCT). The fibers act as glucose sinks that accumulate DIG, enabling its detection by μCT. Quantitative analysis shows that the fibers are more oriented when incubated with DIG. This work demonstrates the advantages of using higher organisms for biological in‐situ transformation of economically important raw materials over conventional chemical surface modification processes, thereby providing a scientific foundation for implementing future alternatives and sustainable manufacturing strategies towards a bio‐based economy.

Analysing the support of sustainability within the manufacturing strategy through multiple perspectives of different business functions

This paper proposes an empirical study aimed at characterizing the evolution of a company towards a sustainable manufacturing strategy, with a special emphasis on the role played by the business functions within the industrial organization. In the study, a methodology to evaluate and rank the sustainable manufacturing strategy in different production contexts is developed, stemming from the fact that there is a lack of objective methods for sustainable manufacturing strategy ranking in the literature. The analysis method consists of an Analytic Hierarchy Process applied to competitive priorities and manufacturing performances. It enables a structured reflection that considers the multiple perspectives of different decision-makers in business functions relevant to the implementation of sustainability in the manufacturing strategy. The main objective of the approach proposed in this study is to provide a methodology able to give an integrated view of the economic, environmental and social dimensions of the manufacturing plants. The proposed methodology is applied in two application case studies referring to two different production contexts. The application cases show the usefulness of the methodology to assess how sustainability is supported in the manufacturing strategy, with specific concern to the evolution of a manufacturing plant towards a sustainable manufacturing strategy.

Development of structural equation model for Lean Six Sigma system incorporated with sustainability considerations

PurposeThe study aims to describe the development of a structural measurement model using structural equation modeling technique to validate the association that exists between Lean Six Sigma (LSS) and sustainable manufacturing strategies.Design/methodology/approachBoth LSS and sustainable manufacturing aim at improving the firm’s business competitiveness which forms a strategic link that benefits the manufacturing organizations. The study aims to investigate the relationship among constructs that leads to operational excellence while deploying LSS and sustainable manufacturing strategies in organizations.FindingsEmpirical data needed for the study are collected from experts belonging to various industries that are implementing both LSS and sustainable manufacturing practices. Later statistical estimates (hypotheses) are being formulated to confirm the developed measurement model. Based on the obtained results after analysis of the structural model, the statistical estimate is either being accepted or rejected. Results of this study reveal that there exists a strong correlation between LSS and sustainable manufacturing factors that leads to organizational performance.Research limitations/implicationsAdditional indicators could be included to deal with technological advancements in sustainable manufacturing.Practical implicationsThe study has been done with regard to Indian automotive component manufacturing organizations scenario. Hence, the inferences derived have practical relevance.Originality/valueThe development of structural model for the Lean Six Sigma system with sustainability considerations is the original contribution of the authors.

Modelling a decision-making network for sustainable manufacturing strategy

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.

Modelling a decision-making network for sustainable manufacturing strategy

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.

AN INTEGRATED TYPE-2 FUZZY DECISION MODEL BASED ON WASPAS AND SECA FOR EVALUATION OF SUSTAINABLE MANUFACTURING STRATEGIES

One of the most essential topics for the present and future generations is sustainability. Today, because of threats made by traditional and old manufacturing practices, sustainability has become an essential topic in manufacturing companies. Attaining a sustainable manufacturing process requires making decisions about the strategies of manufacturing. In this paper, a novel integrated model is developed to evaluate sustainable manufacturing strategies. The proposed model is based upon two multi-criteria decision-making (MCDM) methods: WASPAS (Weighted Aggregated Sum Product ASsessment) and SECA (Simultaneous Evaluation of Criteria and Alternatives). Due to the uncertainty of evaluation process, we use interval type-2 fuzzy sets (IT2FSs). An example of evaluating sustainable manufacturing strategies is presented, and a sensitivity analysis is carried out for illustration of the developed approach and validation of it. The findings show the efficiency of the developed model, and based on the considered example, “Eco-efficiency” can be regarded as an effective strategy.

A novel hybrid multi-criteria group decision making approach for failure mode and effect analysis: An essential requirement for sustainable manufacturing

Modern manufacturing organizations have started giving paramount importance to sustainable aspects of the manufacturing processes, realizingnot only that the natural resources are dwindling rapidly but also that they bear significant responsibility to the society and surroundings for the overall future development. Catastrophic failures and the maintenance of complex equipment can generate a large amount of hazardous waste within the organization that can affect the overall production level, environment, along with impacting the health of workers in the long run. Failure mode and effect analysis (FMEA) is an efficient risk analysis tool for processes, products, designs or services and has been adopted by different types of organizations. In this paper, for the first time in the literature, the consequences of failure modes of industrial equipment are considered from the sustainable point of view, which is believed to be a requirement for the establishment of a successful sustainable manufacturing strategy. Severities of failure modes are considered from environmental, societal and economic points of view, along with the chances of occurrences and detections. However, due to lack of exact data, these risk factors are evaluated linguistically by cross-functional experts, which made the situation complex. To properly prioritize the failure modes according to their risk levels, a novel hybrid Multi-Criteria Group Decision Making (MCGDM) approach by integrating Interval Type-2 Fuzzy Decision-Making Trial and Evaluation Laboratory (IT2F-DEMATEL) and Modified Fuzzy Multi-Attribute Ideal Real Comparative Analysis (Modified FMAIRCA) methods is proposed. Calculating the causal dependencies among the risk factors and finding out their relative importance are the twofold benefits of the IT2F-DEMATEL approach. Defuzzified criteria weights are further utilized in the proposed modified FMAIRCA approach for risk ranking of failure modes. The effectiveness of the proposed hybrid approach is demonstrated by considering a case-study from a process plant gearbox. Next, the obtained ranking results are compared with the results obtained from other commonly applied fuzzy MCDM methods in the FMEA domain. Stability and robustness of the proposed approach is also highlighted by performing sensitivity analysis.

Sustainable manufacturing production-inventory decision of multiple factories with JIT logistics, component recovery and emission control

Based on two sustainable manufacturing strategies: resource recycling and emission reduction, this paper addresses a new production-inventory problem of multiple factories with JIT logistics, component recovery and emission control. Motivated by beer industry, we formulate this problem based on two decision mechanisms: (1) PI-CR decision mechanism–sole consideration of component recovery (component recycling) (2) PI-RE decision mechanism–joint consideration of component recycling and emission control. In the PI-RE decision mechanism, two emission control policies—carbon tax and carbon cap & trade are implemented. Numerical analysis is demonstrated to show the application of the models, and the managerial implications are put forward. Results show that emission control and resource recycling strategies have different impacts on the decision, increasing the return rate of recoverable component is an effective approach to currently reduce emissions and cost, while the cap & trade policy is more effect than the carbon tax policy in controlling emissions.

Evaluation of the Sustainable Efficiency of two Manufacturing Processes using Life-Cycle Assessment and Efficiency Analysis

The global demand for raw materials is increasing consistently in the modern world such that a resource efficient handling becomes more and more important in today’s manufacturing processes. Therefore, re-manufacturing of degraded products and components is a major step within a sustainable manufacturing strategy. This paper shows an approach to evaluate and to compare the sustainability of two manufacturing processes using life-cycle assessment on the one hand and efficiency analysis methods on the other. In a first step, the two processes were analysed regarding their environmental impact in 13 different effect categories using the life-cycle assessment software GaBi. Data envelopment analysis (DEA) as well as TOPSIS were utilized to evaluate and to compare these results regarding sustainable efficiency in a second step. The analysis is done within the case study “Recycling of lead anode”. The evaluation of a new developed concept for an automated process, in comparison to a manual process, to recycle lead anodes, which were subjected to heavy wear during the electrowinning process of non-ferrous metals like copper, nickel or zinc, is in focus.

Application of fuzzy axiomatic design for prioritisation of sustainable manufacturing strategies for an automotive component manufacturing scenario

Sustainable manufacturing enables automotive component manufacturing organisations to develop products with minimal environmental impact. Appropriate strategies need to be deployed to facilitate development of ecofriendly products and processes. This article presents a study in which eight sustainable manufacturing strategies were analysed and prioritised using fuzzy axiomatic design (FAD) methodology. Triangular fuzzy numbers were employed for expressing the inputs related to criteria of sustainable manufacturing, as real world experience has difficulty in measurement together. Expert team inputs were obtained and total information content (TIC) values were calculated for all strategies. Strategy with least TIC value namely 'Auditing tools' was the best alternative. The prioritised strategies were being subjected to implementation in the case organisation. Effectiveness verification of the implementation need to be carried out after a defined period by the organisation through actual measurement.

Application of multi-grade fuzzy and ANFIS approaches for performance analysis of Lean Six Sigma system with sustainable considerations

Lean Six Sigma (LSS) is a manufacturing strategy that aims at improving the firm's competitiveness and operational performance through waste reduction and process variation. Sustainable manufacturing aims at creating manufactured products with minimal negative environmental impacts. In order to facilitate zero defects and improve their sustainable performance, manufacturing firms have started to adopt both LSS and sustainable manufacturing strategies to attain integrated benefits. This article reports a research carried out to analyse the performance of LSS system integrated with sustainability considerations using multi grade fuzzy (MGF) and adaptive neuro fuzzy inference system (ANFIS) approaches. During this research, a performance assessment model was designed. The score based on MGF approach is found to be 6.74 and that of ANFIS approach is 6.51. Based on computation, the case organisation was found to possess 'strong LSS performance with sustainability considerations'. The study could facilitate improvement in LSS performance incorporated with sustainability aspects.

Application of multi-grade fuzzy and ANFIS approaches for performance analysis of Lean Six Sigma system with sustainable considerations

Lean Six Sigma (LSS) is a manufacturing strategy that aims at improving the firm's competitiveness and operational performance through waste reduction and process variation. Sustainable manufacturing aims at creating manufactured products with minimal negative environmental impacts. In order to facilitate zero defects and improve their sustainable performance, manufacturing firms have started to adopt both LSS and sustainable manufacturing strategies to attain integrated benefits. This article reports a research carried out to analyse the performance of LSS system integrated with sustainability considerations using multi grade fuzzy (MGF) and adaptive neuro fuzzy inference system (ANFIS) approaches. During this research, a performance assessment model was designed. The score based on MGF approach is found to be 6.74 and that of ANFIS approach is 6.51. Based on computation, the case organisation was found to possess 'strong LSS performance with sustainability considerations'. The study could facilitate improvement in LSS performance incorporated with sustainability aspects.

Application of fuzzy axiomatic design for prioritisation of sustainable manufacturing strategies for an automotive component manufacturing scenario

Application of fuzzy axiomatic design for prioritisation of sustainable manufacturing strategies for an automotive component manufacturing scenario

Event-Based Production Control for Energy Efficiency Improvement in Sustainable Multistage Manufacturing Systems

There has been an increasing trend for manufacturers to shift toward sustainable manufacturing strategies in response to an ever-growing pressure from fluctuating energy price and environmental crisis. Reducing energy consumption is considered as an important step to achieve the sustainability of a production system. This paper proposes an event-based control methodology to improve the production energy efficiency through strategically switching appropriate stations to energy saving mode. Based on an event-based analysis of production dynamics, an analytical approach is developed to quantitatively predict the system level production loss resulted from an energy saving control event (ESCE). A genetic-based control algorithm is proposed to balance the trade-off between the gain from energy saving and the expense of throughput loss. The energy improvement analysis results in a fundamental understanding of production energy dynamics and a significant decrease of energy cost for a manufacturing facility. Numerical case studies are performed to validate the effectiveness of the proposed method. It is found that the control method can effectively reduce energy cost, while only slightly impacting production.

Metrics-based approach to evaluate sustainable manufacturing performance at the production line and plant levels

Abstract Promoting sustainability in manufacturing is becoming increasingly important due to the scarce natural resources, stricter regulations and increasing customer demand for more sustainable products. In order to meet this demand for sustainable products, manufacturing companies have to adopt numerous strategies for sustainable manufacturing through the use of more sustainable processes and systems. To improve performance of any domain, it must first be measured comprehensively. Approaches for evaluating sustainability performance of products and processes have been investigated in previous work where comprehensive product/process sustainability indices are proposed. While numerous studies address the topic, no comprehensive methods are available for sustainable manufacturing performance evaluation at the system level, particularly at the production line and plant levels. To address this gap, this paper presents an index-based method for comprehensively evaluating sustainable manufacturing performance at the production line and plant levels. First, existing literature have been studied and reviewed thoroughly. Then a set of comprehensive sustainability metrics have been identified and proposed for production line and plant levels, respectively, where the three pillars of sustainability, total life-cycle stage emphasis, and 6R concepts are concurrently addressed. These proposed metrics are organized into five-level hierarchy (metric, sub-cluster, cluster, sub-index, index) where lower level items are consolidated to the higher level. Then index-based methods are proposed to evaluate sustainable manufacturing performance at the production line (LiSI) and plant (PlaSI) levels. Finally, the application of the proposed method is illustrated for a satellite television dish manufacturing company at the production line level.

REMANUFACTURING WITHIN A SUSTAINABLE MANUFACTURING STRATEGY: RECYCLING OF LEAD ANODES

The global demand for raw materials is increasing consistently in the modern world such that a resource efficient handling becomes more and more important in today’s manufacturing processes. Therefore, remanufacturing of degraded products and components is a major step within a sustainable manufacturing strategy. Remanufacturing planning has to consider heterogeneous raw material (used material), which has a direct impact on the refurbishing technology and the remanufacturing layout. This paper shows an analyzing concept regarding the planning of remanufacturing concepts to ensure reliable recycled products based on heterogeneous materials. The shown concept is substantiated with a case study “Recycling of lead anodes”. The evaluation of three concepts for the development of an automated process to recycle lead anodes, which were subjected to heavy wear during the electrowinning process of non-ferrous metals like copper, nickel or zinc, is in focus.

Applying fuzzy AHP–TOPSIS technique in identifying the content strategy of sustainable manufacturing for food production

Food manufacturing is an important value-adding sector of both local economies and the global economy in terms of job creation, food security and participatory community development, among others. Along with highly relevant issues on energy consumption, unsustainable land-use patterns, waste generation associated with the industry, social issues in terms of health and safety of food products are part of the larger sustainability concerns. While maintaining economic stability at the firm level, there is a need to develop a sustainable manufacturing strategy that addresses competitiveness and sustainability. Emerging concerns for sustainable manufacturing are circulating, but focusing on a particular industry remains a gap. Thus, this paper attempts to formulate a sustainable manufacturing strategy and then to map this strategy to established best practices. The main departure of this work is: (1) identifying the content strategy of sustainable manufacturing strategy for food manufacturing firms, (2) determining the most relevant best practice that would largely address the content strategy and (3) providing guidelines for food manufacturing decision-makers and policy-makers in strategy formulation that aims to enhance the sustainability of their manufacturing firms. A fuzzy analytic hierarchy process–technique for order of preference by similarity to ideal solution (AHP–TOPSIS) approach is used to formulate the strategy and then rank the best practices. A case study is carried out in the Philippines, and results show the content strategy and total quality management is the best practice that supports the sustainability of food manufacturing firms followed by resource and material efficiency approaches.

A Methodology to Align Core Manufacturing Capabilities with Sustainable Manufacturing Strategies

How do core business and manufacturing capabilities enable strategies for sustainable manufacturing, and what are those capabilities? This paper proposes a Capability Methodology for Sustainable Manufacturing (CMSM) for allowing top management of manufacturing companies to address these questions. A diagnostic tool was developed from three case studies based on a set of interview questions aimed at identifying core capabilities and sustainability issues in manufacturing companies. Interview data was coded and mapped through a relational matrix formulation that describes four archetypes for the development of sustainability strategies. The matrix maps the degree of complexity of the sustainability concept as understood by the company, and the scope of the product life cycle being considered. It is argued that the methodology helps bring awareness to managers of any gaps or mismatches between their actual core capabilities and the desired outcomes for sustainable manufacturing.

A probabilistic fuzzy analytic network process approach (PROFUZANP) in formulating sustainable manufacturing strategy infrastructural decisions under firm size influence

This paper explores the probabilistic fuzzy analytic network process (PROFUZANP) approach in identifying the content of manufacturing strategy infrastructural decisions that attempt to integrate a sustainability and classical manufacturing strategy framework, in the presence of firm size as a relevant component in decision-making. Linguistic variables with equivalent triangular fuzzy numbers (TFNs) are used to elucidate the judgment of elements in pairwise comparison in the framework of the analytic network process (ANP). The ANP effectively handles the complexity of decision-making brought about by the subjectivity and relationships among components of the decision model. Integration of expert judgments conducted by introducing a normal probability distribution in each pairwise comparison with mean equal to the geometric mean of the judgment and standard deviation equal to a predefined perturbation of judgment around the mean. Pre-selected experts in manufacturing strategy and sustainability were asked to elicit judgment in pairwise comparison. Results show that the content of the infrastructural decisions of manufacturing strategy remains constant regardless of the types of firm size. However, the priority of each decision to the goal, which can be translated as the priority of implementation of each policy, varies between large firms and SMEs. The main contribution of this paper is a novel approach that holistically captures the judgmental uncertainty of individual decision-makers and the uncertainty of group decision-making.

The Impact of Firm Size in the Formulation of Sustainable Manufacturing Strategy Infrastructural Decisions Under Uncertainty

This paper adopts a fuzzy analytic network process approach in identifying the impact of the presence of firm size on the content of the manufacturing strategy infrastructural decisions that integrates the classical manufacturing strategy framework and the notion of sustainability. Linguistic variables with equivalent triangular fuzzy numbers were used to elucidate judgment of elements in pairwise comparison matrices within the context of the analytic network process. Analytic network process effectively handles the complexity of the decision-making problem resulting from the subjectivity and interrelationships inherent among decision components. Domain experts in manufacturing strategy and sustainability were asked to elicit judgment in pairwise comparisons. Results show that the content of the infrastructural decisions of manufacturing strategy remains constant regardless of the presences of firm size component. However, the priority of each decision to the goal which can be translated as the priority of implementation of each policy varies with the presence of firm size.