Sustainable Manufacturing Operations Research Articles

THE RELATIONSHIP BETWEEN SUSTAINABLE MANUFACTURING OPERATIONS AND ENVIRONMENTAL PERFORMANCE OF PLASTICS AND RUBBER MANUFACTURERS IN KENYA: THE MODERATING EFFECT OF ECO-INNOVATIONS

Objective: This study aimed to expose the effect of sustainable manufacturing operations on performance of plastics and rubber manufacturing firms in Kenya. Theoretical Framework: The main concepts and theories that support the research were conveyed. The study employed the natural resource-based view and ecological modernisation theory. Method: The study employed descriptive research survey that targeted all the 90 plastics and rubber manufacturing firms registered by the Kenya Association of manufacturers. A structured questionnaire as well as a data collection form were useful in collecting data. For data analysis descriptive and inferential statistics were used with the precise inclusion of partial least squares structural equation modeling method. Results and Discussion: There was a statistically significant influence of eco-innovations on the effect of sustainable manufacturing operations on environmental performance. However, the individual eco-innovations indicators namely eco-product innovations, eco-process innovations, green system innovations and material flow innovations yielded varied results. Research Implications: The findings confirm previous studies that indeed there are positive gains made from the moderating role of eco-innovations in the correlation between sustainable manufacturing operations and performance of the environment. Originality/Value: These results are expected to benefit stakeholders such as policy makers in government, plastic and rubber manufacturers and academia in augmenting the existing knowledge.

Characterizing Circular Supply Chain Practices in Industry 5.0 With Respect to Sustainable Manufacturing Operations

The current research investigated the significance of circular supply chain practices in Industry 5.0 with respect to their sustainable manufacturing operations. Through a comprehensive review of the literature, the current study identified key circular supply chain practices and their potential benefits for Industry 5.0. The findings indicated that closed-loop supply chains, sustainable sourcing, product design for circularity, and waste reduction may assist Industry 5.0 firms to achieve their sustainability objectives while enhancing the operational efficiency. Moreover, the study also highlighted the challenges associated with the implementation of circular supply chain practices including the necessity for collaboration among supply chain partners, investment in new technologies and infrastructure, and the development of new skills and capabilities. From a practical and managerial perspective, the implications suggest that firms aiming to adopt circular supply chain practices in Industry 5.0 should prioritize collaboration and coordination, make investments in new technologies and infrastructure, and foster the acquisition of new skills and capabilities. To complement this research, future studies could employ empirical research methods in order to validate the findings and recommendations as well as explore potential barriers to the implementation of circular supply chain practices in Industry 5.0.

An Efficient Siamese Network and Transfer Learning-Based Predictive Maintenance System for More Sustainable Manufacturing

Legacy machinery poses a specific challenge when integrated into modern manufacturing lines. While modern machinery provides swift methods of integration and inbuilt predictive maintenance (PdM), older machines, while physically fully functional, are less attractive to reuse, a specific reason being their lack of ready-to-implement PdM hardware and models. More sustainable manufacturing operations can be achieved if the useable lifespan of functional older machinery can be extended through retrofittable PdM and modern industrial communication systems. While PdM models can be developed for a class (make/model) of machine with retrofitted sensing, it is often found that legacy machines will deviate greatly from their original form, through nonstandard maintenance and component replacement actions during their lengthy lifespan. This would mean that each legacy machine would require a custom PdM model, a cost often leading to the removal or nonusage of legacy machines. This paper proposes a framework designed for the generation of an efficient PdM algorithm which would allow for the reuse of legacy machines retrofitted with low-cost sensing in modern manufacturing for increased sustainability. Given a limited number of data samples collected from a machine to be maintained, we aim to predict a failure or/and maintenance time by making use of the difference between the characteristics of the variation of the healthy and unhealthy data collected from the machine. We measure the healthiness of the machine by using a Siamese network trained with a public dataset and fine-tuned with data samples obtained from machines with similar characteristics. Although we use different training and testing datasets coming from completely different sources, we obtain reasonable results thanks to the proposed technique. The results of simulations and the statistical analysis enable us to devise a transfer learning technique and a Siamese network employed for failure detection in the machine. The proposed system will allow for the continued use of older machines in modern facilities, enabling more sustainable manufacturing models.

Big data analytics challenges to implementing the intelligent Industrial Internet of Things (IIoT) systems in sustainable manufacturing operations

The overlap of the growth of big data with that of the Internet of Things (IoT) is well reflected by the dramatic surge in the use of devices connected to IoT and the exponential rise in data consumption. Huge numbers of sensors and devices deployed in the industry sector have resulted in the production of massive big data in the industrial IoT (IIoT). The literature consists of many studies conducted on big data analytics (BDA) and IIoT, though it still lacks research into the most important challenges to the growth of intelligent IIoT systems. This paper presents an innovative integrated method using the multi-objective optimization on the basis of a ratio analysis plus the full multiplicative form (MULTIMOORA) and criteria interaction through inter-criteria correlation (CRITIC) under the q-rung orthopair fuzzy sets (q-ROFSs). In the proposed method, CRITIC is used to calculate the attribute weights, whereas MULTIMOORA is utilized to estimate the ranking of options on the q-ROFSs. Then, a case study is accomplished on the challenges of BDA in the process of developing intelligent IIoT systems in the environment of industry 4.0. Furthermore, comparative and sensitivity analyses are conducted on the proposed approach to prove the capability of the developed framework in the prioritization of intelligent IIoT systems.

Optimising Changeover through Lean-Manufacturing Principles: A Case Study in a Food Factory

Operations management is a key aspect in any manufacturing business. Optimising the management of manufacturing operations allows improvement of the productivity and efficiency of industrial activities. To achieve this, reducing waste from manufacturing processes and, therefore, implementing lean-manufacturing principles, is key. This article presents a case study to reduce waste in changeover processes at a ready-meal manufacturer based in South Yorkshire, UK. We identified a large number of activities as part of the changeover process. We applied the Single Minute Exchange of Dies (SMED) methodology to reduce and, whenever possible, eliminate changeover, and line hopping to further optimise changeover. After implementing improvement measures, changeover time was reduced by nearly 30%, OEE was increased to over 70%, and labour costs were reduced by 10%. This shows how lean principles can aid in implementing more effective and economically sustainable manufacturing operations.

Analysis of barriers intensity for investment in big data analytics for sustainable manufacturing operations in post-COVID-19 pandemic era

PurposeThe study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.Design/methodology/approachThe study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.FindingsThe study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.Practical implicationsThis study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.Originality/valueThe novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.

Manufacturing sustainability: Institutional theory and life cycle thinking

This study sets out to bridge resource perspective on material selection with stakeholder and institutional theory considerations to provide a more comprehensive understanding of life-cycle thinking on material selection decisions in the automotive industry. The objective is to shed light on how regulatory, normative and mimetic institutional pressures, affect sustainability decisions when switching or substituting materials or manufacturing processes in the automotive industry. Within a hybrid life cycle analysis framework, the environmental hotspots across the supply chains of two empirical management examples of Aluminium and CFRP LCA models are presented, quantified and ranked. Further justifications are provided on why and how regulatory, normative-peer and peer-normative pressures affect life cycle decisions. Findings reveal early, mid-process and late-stage life cycle hotspots, both in the material selection and the manufacturing process for both components. This decision support framework can be used to diverge from high energy-intensive manufacturing process and conventional raw materials, and provide forward-looking automotive manufacturers with opportunity to make asset-specific investments in lightweight, fuel-efficient vehicles, and sustainable manufacturing operations. This study presents a new framework that hybridises institutional theory and life cycle thinking to enable a standard routine and decision assessment of sustainability. This study provides a novel theoretical perspective on life cycle assessment by highlighting how the framing rules in a given institution mirror the trajectory of institutional pressures from regulatory (organised laws) through normative (organised behaviour) to mimetic (copied behaviour).

Big data analytics application for sustainable manufacturing operations: analysis of strategic factors

In the present era of Industry 4.0, organizations are transforming from traditional production systems to digital production systems. This transformation is in terms of additional deployment of technologies that lead to digitization and integration of products and services, business processes and customers, etc. A high volume of unstructured data is being created across different processes due to digitization. The digitization captures the data that includes text, images, multimedia, etc., due to multiplicity of platforms, e.g., machine-to-machine communications, sensors networks, cyber-physical systems, and Internet of Things. Managing this huge data generated from different sources has become a challenging task. Big data analytics (BDA) may be helpful in managing this unstructured data for effective decision making and sustainable operations. Many organizations are struggling to integrate BDA with their manufacturing processes for sustainable operations. The application of BDA from a sustainability perspective is not extensively researched in the current literature. Therefore, firstly this study explores the contribution of BDA in sustainable manufacturing operations. It further identifies strategic factors for the successful application of BDA in manufacturing for sustainable operations. For a detailed analysis of strategic factors in manufacturing, a hybrid approach comprising the analytic hierarchy process, fuzzy TOPSIS and DEMATEL is used. Results revealed that development of contract agreement among all stakeholders, engagement of top management, capability to handle big data, availability of quality and reliable data, developing team of knowledgeable, and capable decision-makers have emerged as major strategic factors for the application of BDA in the manufacturing sector for sustainable operations. Major contribution of this study is in analyzing BDA benefits for manufacturing sector, identifying major strategic factors in implementation and categorization of these factors into cause and effect group. These findings may be used by managers as guidelines for successful implementation of BDA across different functions in their respective organization to achieve sustainable operations goal. The results of this study will also motivate industry professionals to integrate BDA with their manufacturing functions for effective decision making and sustainable operations.

Impact and optimisation of a new paradigm in engineering economics for sustainable manufacturing operations

As natural resources and other materials required for manufacturing become scarcer and more expensive, it is no longer feasible to simply design and manufacture products without extensively considering the costs involved. Also, there is far greater awareness of the adverse side-effects of engineering advances in production and manufacturing, such as, by-products from plants. Due to these reasons, engineers are required to put far more effort into ensuring all design projects and manufacturing operations fall within a favourable economic framework in line with environmental regulations for a given region of operation. Practically, engineers nowadays must evaluate and decide whether the benefits of executing a project or process are more significant than the associated costs, a task achieved through engineering economics. This paper seeks to discuss the concept of engineering economics in relation to operations management. Relevant terms are briefly outlined, and the implementation and optimization of a novel technique for managing engineering operations using engineering economics are presented. The proposed paradigm's possible benefits are also highlighted, and conclusions are offered at the end of the paper.

Exploring the impacts and contributions of maintenance function for sustainable manufacturing

This investigation studies advanced practitioners of maintenance management and seeks to uncover the related impacts and contributions of best practice maintenance toward sustainable manufacturing operations. This exploratory research conducted a novel empirical analysis focused on maintenance functions in nine manufacturing companies from diverse sectors. The analysis uncovered insights related to the economic, environmental, and social benefits of deeper involvement of maintenance function in plant operations and decision-making. We observed links of maintenance function with product competitiveness and with energy management activities that were unexpected. We confirmed benefits from keeping machinery in good working conditions and restoring promptly good working conditions when an issue happens. The depth of maintenance contribution on each area identified in this study will depend on the operational and business context of the manufacturing company; thus, companies need to reflect on these based on their specific processes, business needs and goals. Ultimately, this work can inspire managers in manufacturing companies to organise maintenance functions strategically toward fostering long-term competitive, responsible and sustainable performance.

A multi-site production and microgrid planning model for net-zero energy operations

This paper aims to address two critical questions pertaining to sustainable manufacturing operations. First, how to model and design a multi-facility, production-logistics system under product demand and energy supply uncertainty? Second, is it economically viable to achieve net-zero energy operations through renewable microgrid integration? To answer both questions, we present a joint production scheduling and microgrid sizing model to decarbonize the manufacturing, transportation and warehousing operations by harnessing onsite wind and solar energy. The integrated planning model is solved as a two-stage optimization program: first, scheduling the production to meet the uncertain demand; second, sizing and siting the microgrid systems to meet the electric load of multiple facilities. The preliminary results show that net-zero energy operation is feasible and affordable in locations where the capacity factor of wind and solar generation exceeds 0.25 and 0.45, respectively. Sensitivity analysis shows that battery system combined with solar photovoltaics is cost-effective despite the high capital cost of storage devices. Two managerial insights are also derived. First, integrating onsite renewable power is the ultimate key to realizing net-zero energy industrial operations. Second, grid-connected microgrid generation with net metering results in lower capacity investment than island operation.

From linear to circular manufacturing business models

Purpose - This editorial piece introduces the special issue titled ‘From Linear to Circular Manufacturing Business Models’. Design/methodology/approach - The ‘Background and Motivation’ section provides an overview of the current practical environmental challenges faced by the manufacturing sector, mainly due to the use of linear business models, and it argues the potential benefits of adopting the circular economy concept as a potential solution to address such challenges. This section also exposes the limitations of scholarly research in this field. On the other hand, the ‘Features and Areas of the Special Issue Contributions’ section discusses the themes and related inter-disciplinary topics that were considered in the special issue. Findings - The editorial concludes with a summary of the accepted papers in terms of the specific topics they address and their main contributions to the domain of manufacturing technology management, with specific focus on how circular economy can intervene, support and contribute to deliver more economic, social and environmentally sustainable manufacturing operations and processes, and in this way help to address some of the most critical challenges we are currently confronting as humankind, i.e. environmental degradation. Originality/value - Four articles that characterise good and state-of-the-art research work spans from a variety of leading edge research in the area of circular economy, with particular application in the design, management and improvement of manufacturing operations, processes and technology were selected. These papers illustrate the different practical approaches and theoretical perspectives considered by the authors to effectively use/integrate CE into manufacturing operations and processes.

Sustainable machining as a mean of reducing the environmental impacts related to the energy consumption of the machine tool: a case study of AISI 1045 steel machining

Due to the rising concerns related to the depletion of fossil fuel sources, and the climate change associated to the usage of such sources for electricity generation, there is a high pressure for diminishing the energy consumption of all the industrial sectors in order to mitigate the negative impacts associated to the energy required to manufacture a product. Computer numerical control (CNC) machining accounts for a larger portion of the total energy drawn from the grid by the manufacturing sector. Therefore, the energy efficiency of the manufacturing operations should be enhanced to optimize their energy consumption and to reduce their environmental burden as well. As a mean for achieving sustainable manufacturing operations, the present paper outlines an experimental study to optimize cutting parameters in turning of AISI 1045 steel. One of the main objectives was to minimize the total specific energy consumed by the CNC machine tool during material removal, considering dry cutting to decrease the environmental impacts linked to the coolant usage. As a measure of the surface quality, the second objective was to reduce the average surface roughness of the workpiece. The same material removal volume was considered for all the experimental trials. The response surface method was used to obtain the regression models for all the variables studied, and the desirability method was selected for defining the values of these variables, named the cutting parameters, that minimized the quantity of electrical energy consumed, and surface roughness. The results achieved showed that it is possible to obtain a more sustainable machining process without sacrificing the productivity of the process and the final quality of the product.

Sustainability in manufacturing operations scheduling: A state of the art review

Sustainability in manufacturing systems is an urgent requirement for today's manufacturing companies. This paper focuses on sustainable manufacturing operations scheduling, a subject which has been attracting increasing interest from researchers in recent years. This paper presents a state of the art review of this field. First, it characterizes what can be considered as sustainable manufacturing operations scheduling, and introduces the relevant challenges and issues. An analysis of the literature is then proposed, and organized according to three keys. The shortcomings in the literature are then discussed in depth, and subsequently urgent problems that must be solved through research in order to meet industry requirements are pointed out.

Go-green manufacturing holons: A step towards sustainable manufacturing operations control

Despite their potential benefits in the context of sustainable manufacturing operations, holonic and multi-agent architectures are still not designed methodologically to support this major societal and environmental challenge. To address this shortcoming, the generic concept of go-green manufacturing holon is proposed. The idea is to incite researchers to develop sustainability-oriented manufacturing operations control architectures, holonic or multi-agent, and to provide a usable generic concept that is easy to appropriate, particularize and implement. An illustration of the concept is proposed, as well as its extension to the context of circular economy.

Identifying the characteristics for achieving sustainable manufacturing companies

PurposeThe purpose of this paper is to identify the qualitative characteristics that can make manufacturing small to medium‐sized enterprises (SMEs) more robust and hence become economically sustainable in this globally competitive environment. The characteristics identified will form the foundations for defining a new manufacturing management perspective to both academics and industrialists.Design/methodology/approachThrough a comprehensive case study approach the authors initially analyse the developmental cycle of the subject company and then identify the key characteristics which enabled the company to become economically sustainable and survive in the changing environment in which it operates. The paper opens with a brief academic analysis of sustainability literature available, before developing the case study.FindingsTraditional business improvement strategies, such as Lean and Agility, which many companies initially follow in an attempt to become more robust and economically stable, allow companies to deliver bottom‐line savings in production terms although their effectiveness depends upon the volume and demand profile of their products. Through the case study outlined in this paper however, a combined approach towards the application of Lean is outlined as a primary means of reducing operating costs alongside the simultaneous implementation of product innovation strategies which allows the company to break into new markets as a means to achieving long‐term economic sustainability and making it more robust to market changes. The development of a business within a business is described as an effective mechanism towards achieving business sustainability.Research limitations/implicationsThe paper proposes a novel approach to achieving economic sustainability within a business and can be of benefit to the wider industrial and academic community. The development of work around a single company has its obvious limitations and it is crucial that further work, with a range of companies in the area of business sustainability, is key to developing a comprehensive set of sustainability characteristics.Practical implicationsThe paper proposes a set of qualitative characteristics for the development of an economically sustainable manufacturing company. The development of a comprehensive case study with a subject company also directs and enables other companies of similar size and style to apply a similar approach and to achieve economic sustainability in an efficient and effective manner, through reducing production costs, minimising company failure and increasing business efficiency and effectiveness.Originality/valueThe development of a set of sustainability characteristics aimed at tackling directly the issues of economic sustainability is proposed and is considered by the authors as one of a kind. The case study approach also provides for a framework towards the implementation of sustainable manufacturing operations within SMEs.

Fit manufacturing: a framework for sustainability

PurposeWith the current global downturn, companies must develop new and innovative approaches to ensure that economic sustainability is achieved. The purpose of this paper is to propose a Fit Manufacturing Framework (FMF), the adoption of which can help manufacturing companies to become economically sustainable and operate effectively in a global competitive market. This contribution extends the previous work by the authors and provides an evolution on the initial work through enhancing the development of Fit manufacture through developing a more robust framework and a more comprehensive functional testing of the framework.Design/methodology/approachThe proposed FMF provides a new manufacturing management perspective and a new manufacturing management strategy for creating economically sustainable manufacturing organisations. It builds upon the principles of existing manufacturing paradigms, along with innovative management concepts, to set up the conditions necessary for sustainability. A pilot application of the framework in three SMEs shows positive initial results when assessed against four Measures of Performance.FindingsManufacturing strategies such as Lean and Agility allow companies to deliver bottom‐line savings in production terms, although their effectiveness depends upon the volume and demand profile of their products. The trend towards mass customisation requires companies to provide personalised products and services at mass production prices. This now places a further burden on companies and therefore a holistic manufacturing framework must be developed in order to ensure that the factory of the future is able to meet this new demand. This paper proposes a Fit manufacturing paradigm which integrates the manufacturing efficiencies achieved through Lean and Agility with the need to break into new markets through effective marketing and product innovation strategies to achieve long term economic sustainability. The small‐scale application of the approach in a case company shows the initial results to be positive when measured against key MOPs developed within this paper.Originality/valueThe development of a Fit paradigm aimed at tackling directly the issues of economic sustainability is proposed and is considered by the authors as one of a kind. Fit will also provide a framework for the implementation of sustainable manufacturing operations within organisations.

Integrated production machines and systems – beyond lean manufacturing

PurposeThe purpose of this paper is to propose a “Fit” manufacturing paradigm for industry so that manufacturing companies can become economically sustainable and can operate effectively in a global competitive market. The proposed Fit paradigm is aimed at providing a new manufacturing management perspective to both academics and industrialists.Design/methodology/approachThe Fit paradigm is developed and proposed as a new manufacturing management strategy towards creating economically sustainable manufacturing organisations. Fit is a theoretical development using the principles of existing manufacturing paradigms along with new and innovative management concepts to create a sustainable approach to manufacturing.FindingsManufacturing strategies such as lean and agility allow companies to deliver bottom‐line savings in production terms although their effectiveness depends upon the volume and demand profile of their products. The trend towards mass customisation requires companies to provide personalised products and services at mass production prices. This now places a further burden on companies and therefore a holistic manufacturing framework must be developed in order to ensure that the factory of the future is able to meet this new demand. This paper proposes a fit manufacturing paradigm which integrates the manufacturing efficiencies achieved through lean and agility with the need to break into new markets through effective marketing and product innovation strategies to achieve long term economic sustainability. The small scale application of the approach in a case company shows that the initial results to be positive when measured against a fit index which is developed within this paper.Originality/valueThe development of a fit paradigm aimed at tackling directly the issues of economic sustainability is proposed and is considered by the authors as one of a kind. Fit will also provide a framework for the implementation of sustainable manufacturing operations within organisations.

Micro-flood (MF) technology for sustainable manufacturing operations that are coolant less and occupationally friendly

This paper presents a new technology for minimizing the use of metalworking fluids (MWFs) during the machining process that is atomization-less and occupational friendly. Micro-flood (MF) technology utilizes direct contact between the cutting tool and the MWF without the interaction of a gas medium. Experiments were conducted in high volume mass production environment turning HSLA (high strength low alloy) SAE 070Y steel. Machining performance and total air mass particulates were investigated in dry machining, Near dry machining (NDM) via atomized spray mist and MF technology. Open-atmosphere air monitoring indicated that total mass particulates behaved in an almost linear fashion with respect to gas atomization pressure, whereas the MWF flow rate demonstrated logarithmic trends in NDM applications using an atomized spray. Nozzle orientations directed upward into the air also produced higher mg/m 3 concentrations (such as flank) than chip and rake face orientations that were directed down. Greater separation existed at higher gas atomization pressures, MWF flow rates and by changing the MWF type. At extreme limits, nozzle orientation affected mg/m 3 concentration as much as 4–5 mg/m 3 for water-miscible MWFs and 15–22 mg/m 3 for non-water-miscible MWFs. Tool-life performance varied greatly among MWF type and flow rate, and in all cases MF technology performed better than NDM using an atomized spray mist. Direct and consistent MWF penetration to cutting zone using MF technology lowered tool-wear on the average of 12–75% compared to NDM at the same MWF flow rate. Compared to dry machining, NDM improved tool-wear on the average by 20–243%. In one case, tool-wear performance was improved by 616% at 0.15 mm using MF technology compared to dry machining at a nominal 0.925 mm tool-wear. Overall, a large mass reduction of particulates can be achieved employing MF technology that would have been unrealistic for an open-atmosphere machining environment employing an atomized spray mist. On the average, MF technology can maintain a total air mass particulate of less than 0.4 mg/m 3 in the occupational work zone using MWF flow rates up to 1260 ml/h, regardless of the MWF classification. Atomized spray mist applications are capable meeting the 5 mg/m 3 OSHA limit if MWF flow rates are less than 160 ml/h, air pressures are less than 0.137 MPa (20 psi) using water-miscible MWFs and air pressures are less than 0.0344 MPa (5 psi) using non-water-miscible MWFs.