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The purpose of this paper is to understand how the characteristics of low-volume manufacturing industries influence the product introduction process and factors which can facilitate that process in low-volume manufacturing industries.

A literature review and a multiple-case study were used to achieve the purpose of the paper. The multiple-case study was based on two product development projects in a low-volume manufacturing company.

The main identified characteristics of the product introduction process in low-volume manufacturing industries were a low number of prototypes, absence of conventional production ramp-up, reduced complexity of the process, failure to consider the manufacturability of the products due to an extensive focus on their functionality and increased complexity of resource allocation. It was determined that prior production of similar products could serve as a facilitator of the manufacturing process.

The main limitation of this study is that the identified characteristics and facilitating factors are confined to the internal variables of the studied company. A study of the role of external variables during the product introduction process such as suppliers and customers could be the subject of future studies.

This research will provide practitioners in low-volume manufacturing industries with general insight about the characteristics of the product introduction process and the aspects that should be considered during the process.

Whereas there is a significant body of work about product introduction process in high-volume manufacturing industries, the research on characteristics of the product introduction process in low-volume manufacturing industries is limited.

Sustainability is an integrating concept and demands strategic attention in developing countries like India. Due to strict environmental regulations and ongoing government sustainable policies such as “Namami Gange,” leather industries are extensively facing challenges to conform themselves toward these sustainable policies. The major challenge faced by leather industries is the exponentially increasing cost of adaptation to sustainable product and process. Under these operational constraints, survival of Indian leather industries has become a major challenge. In this context, this paper aims to identify and evaluate sustainable manufacturing policies. The key performance indicators (KPIs) based on triple bottom line of sustainability can assist leather industries that are about to initiate adopting sustainable practices.

This paper demonstrates the role of KPIs for evaluating sustainable manufacturing policies for leather industries in India. Initially, an in-depth literature review analysis has been carried out to identify indicators for evaluation of sustainable manufacturing policies. In this work, an integrated methodology has been developed to refine the priority map of the aforementioned KPIs based on consensus building among experts using Kappa analysis. Total interpretive structural modeling (TISM) has been used to demonstrate relationships which explain the significance of the KPIs. Further, Matriced Impact Croises Multiplication Applique analysis has been carried out to explore the relationships amongst KPIs.

Based on above analysis, identified interactive relationships among the KPIs will assist managers and decision-makers to incorporate effective sustainable policies in leather industries.

It is expected that these identified interactive interrelationships between KPIs will certainly facilitate the leather industry to achieve higher sustainable performance and competitiveness.

This study carries out an in-depth literature review analysis of sustainable manufacturing policies in leather industry. The author proposes an integrated methodology using kappa analysis, consensus building and TISM for evaluation of sustainable policies based on the literature review analysis and expert opinion.

In today’s competitive market, product demand and its mix frequently vary due to various uncertainties, which thus imparts the overall manufacturing cost. Furthermore, uncertainties also impart the layout design in manufacturing industries in the long run. Therefore, the layout design needs to capture the possibility of uncertainties, and these uncertainties must be captured while designing the layout of a facility. Hence, an efficient facility layout design minimizes the manufacturing cost and lead time. The purpose of this paper is to propose a cellular layout design for a tower manufacturing industry.

The paper develops an embedded simulated annealing-based meta-heuristic to solve proposed cellular layout under different scenarios considering single and multi-time periods for tower manufacturing industry. A comparative study is also performed to analyze comparison among static cellular layout, a dynamic cellular layout or a robust stochastic cellular layout for the tower manufacturing industry.

The current layout of the industry is a process layout. Here, the layout for a tower manufacturing industry is proposed under SCFLP, DCFLP and RSCFLP. The proposed models and solution methodology is tested using six scenarios with different combination of time periods. Lastly, OFV value obtained for all the scenarios is compared, and it is found that RSCFLP outruns other SCFLP and DCFLP for a tower manufacturing industry. Based on the above study, it is also concluded that RSCFLP is an efficient and effective layout in tower manufacturing industry.

The paper proposes a cellular layout design for a tower manufacturing industry. The cellular layout design is found to be preferred over the traditional layout as it reduces material handling cost, manufacturing lead time and hazards. Moreover, it enhances productivity and quality.

The purpose of this study is to explore the required changes, outline business potential and envisage the key steps that a networked manufacturing industry needs to take to reach more sustainably performing manufacturing in the future.

The paper utilises a visionary road-mapping approach to study the required changes and the business potential related to sustainable development in the manufacturing industry.

The results were summarised in three sub-roadmaps empowerment of stakeholders, increase efficiency and creation of new performance criteria. On the basis of the summary of the sub-roadmaps, the framework was configured to describe the opportunities and challenges of sustainable business development in the European manufacturing industry.

A clear implication of this study is that a more system-oriented approach, new models for collaboration between network actors and transparently shared network-level KPIs are required before further steps towards a sustainable manufacturing industry can be taken. In addition, sustainability-driven business models are required to specify these changes concretely.

The presented sub-roadmaps and framework summarising them could provide new insights to business practitioners exploring business potential of sustainability.

Understanding about the road-mapping process as tool that enables interaction and envisioning between different stakeholders could also have social implications supporting shared industry-level learning processes.

Studies of sustainability within the manufacturing industry have focused mainly on green issues in supply-chain management or corporation-level governance models and reporting practices. The paper presents a broader view of sustainable development and recognises networked business as part of the solution.

Considers how far the aerospace industry has travelled on the long journey towards lean and agile manufacturing. Starts by comparing the industry with a well‐established model of a lean and in some cases agile manufacturing system already well established in the automotive manufacturing industry. Makes some attempts to overcome the difference in output volume of the two industries. Asks whether lean manufacturing can be applied to the aerospace industry. Draws on observations made both by academics and during visits to aerospace supply companies. Evidence is put forward as to deployment of lean practices in the industry and why lean manufacturing must be deployed throughout the industry. Focuses on the tentative steps towards the first phases of agile manufacturing, through Lean production, in an industry that produces a high technology leading‐edge product using outdated manufacturing systems.

The purpose of this paper is to evaluate the significance of various technology push (TP) and demand pull (DP) practices substantial for achieving sustainable development in Indian manufacturing industries. The research crucially examines the effectiveness of TP-DP practices in manufacturing companies.

An extensive survey of 92 companies in India has been executed to identify improvements made by TP-DP practices, to achieve sustainable development in manufacturing industries. The companies in the survey include medium- and large-scale manufacturing enterprises. The correlations between various TP-DP practices and sustainable development parameters are evaluated and validated using various numerical methods and tools.

The focus of the paper is on the distinguishable contributions made by TP-DP practices like innovative capability, research and development, corporate strategy, export orientation, stringent implementation of government regulations, transforming capabilities, unionized labor and customer attributes toward achieving sustainable development in manufacturing industries. The inter-relationships between different TP-DP practices with sustainable development parameters are evaluated to effectively manage the goals and objectives of industries related to sustainability and growth. However, it is also acknowledged that manufacturing firms need to work more actively on managing certain practices of TP-DP.

In the present investigation, contributions made by TP-DP practices are evaluated to accomplish sustainable development in Indian manufacturing industries. Hence, the results obtained may need some modifications before applying to other countries. Moreover, issue-wise independent modeling can also be performed to assess the importance of TP-DP practices under specific orientations.

The research gives priority to enhancement in the planning among various TP-DP practices and sustainable development indicators in the industries, to impart TP-DP as important practices to meet the challenges of competent markets worldwide.

It has been exhibited from the observations that adequate TP-DP practices can efficiently contribute toward recognition of sustainable development to compete in the highly progressive global market. The results of various inter-relationships among TP-DP practices and sustainable development parameters represent the effectiveness of TP-DP practices for accomplishment of social as well as organizational objectives.

The investigation shows that TP-DP practices are significant initiatives employed by the manufacturing industries for performance improvement and sustainable development. The paper peeks into the research to find out TP-DP issues that need to be assessed efficiently by companies to avail the benefits of sustainable development to meet the challenges posed by international markets.

With the deep development of the new technological revolution and industrial transformation, the development, application, expansion and integration of digital technology provide opportunities for transforming the manufacturing industry from traditional manufacturing to intelligent manufacturing. However, little research currently focuses on analyzing the influencing factors of intelligent development in this field. There is a lack of research from the perspective of the digital innovation ecosystem to explore the intrinsic mechanism that drives intelligent development. Therefore, this article starts with high-end equipment manufacturing enterprises as the research subject to explore how their digital innovation ecosystem promotes the effectiveness of enterprise intelligent development, providing theoretical support and policy guidance for enterprises to achieve intelligent development at the current stage.

This article constructs a logical framework for the digital innovation ecosystem using a “three-layer core-periphery” structure, collects data using crawling for subsequent indicator measurement and assessment and uses the fuzzy set Qualitative Comparative Analysis method (fsQCA) to explore how the various components of the digital innovation ecosystem in high-end equipment manufacturing enterprises work together to promote the development of enterprise intelligently.

This article finds that the various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises, through mutual coordination, can help improve the level of enterprise intelligence. Empirical analysis shows four specific configuration implementation paths for the digital innovation ecosystem of high-end equipment manufacturing enterprises to promote intelligent development. The core conditions and their combinations that affect the intelligent development of enterprises differ in each configuration path.

Firstly, this article discusses the practical problems of intelligent transformation and development in the manufacturing industry and focuses on the intelligent development effectiveness of various components of the digital innovation ecosystem of high-end equipment manufacturing enterprises in the context of digitalization. Secondly, this article uses crawling, text sentiment analysis and other methods to creatively collect relevant data to overcome the research dilemma of being limited to theoretical analysis due to the difficulty in obtaining data in this field. At the same time, based on the characteristics of high-end equipment manufacturing enterprises, the “three-layer core-periphery” digital innovation ecosystem framework constructed in this article helps to gain a deep understanding of the development characteristics of the industry's enterprises, provides specific indicator analysis for their intelligent development, opening the “black box” of intelligent development in the industry's enterprises and bridging the gap between theory and practice. Finally, this study uses the fsQCA research method of configuration analysis to explore the complexity of the antecedents and investigate the combined effects of multiple factors on intelligent development, providing new perspectives and rich research results for relevant literature on the intelligent development of high-end equipment manufacturing enterprises.

This thesis deeply studies the impact mechanism of digital service trade on the high-quality development of the manufacturing industry from the aspects of technological innovation and industrial structure.

In this thesis, 40 countries from 2010 to 2020 were selected as samples, and the panel fixed-effect model and intermediary effect model were used to empirically analyze the impact path of digital service trade on the high-quality development of global manufacturing.

Overall, digital service trade has a positive impact on the high-quality development of the global manufacturing industry. Through the analysis of the intermediary effect mechanism, it is found that digital service trade can further positively affect the high-quality development of the global manufacturing industry by promoting technological innovation and industrial structure upgrading.

Based on the empirical results, targeted countermeasures and suggestions are given in this paper.

Through the test of national heterogeneity, it is found that in developing countries, digital service trade mainly acts on the high-quality development of the manufacturing industry by promoting industrial structure upgrading.

In developed countries, digital service trade mainly promotes the high-quality development of manufacturing through technological innovation; from the perspective of industry heterogeneity, the three service industries of information and communication technology (ICT), other business services and property have the intermediary effect of technological innovation and industrial structure.

This manuscript suggests that trade in digital services should be promoted as a national trade priority.

This paper explores how education and training systems can support a digitally-enabled workforce for the Australian manufacturing sector.

The study is based on interviews with 17 sector-level manufacturing stakeholders from industry, government and education/training organisations. Semi-structured interviews were conducted to gain an in-depth understanding of how education and training systems currently support a digitally-enabled manufacturing workforce as well as opportunities for alternative configurations or developments.

Analysis revealed three themes reflecting core dimensions of a supportive education and training system: partnerships, pedagogy and prospects. Cooperative, integrated and sustained partnerships are needed between vocational education and training (VET) institutions, universities, government, industry, high schools and private training providers. Pedagogy emphasises the vital importance of infusing curriculum with digital and technology skills and capabilities, alongside innovative and experiential delivery modes including simulated environments, online learning, on-the-job training, flexible delivery and micro-credentials. Prospects reflects the need for forward-looking assessment and planning to respond to industry trends and develop associated qualifications, skills and investments required to meet future industry needs.

With growing demand for digitally-enabled skills to support manufacturing, an industry which is acknowledged as critical for economic prosperity and national sovereignty, the findings contribute novel insights into current limitations and future opportunities to bridge the gap between skills shortages in the manufacturing industry, and education and training systems that deliver graduate readiness and a digitally-enabled workforce.

Because of the COVID-19 pandemic and changing market demands, competition for manufacturing industries is increasing and they face numerous challenges. In such a case, it is necessary to use multiple strategies, technologies and practices to improve organizational performance and, as a result, to integrate them for ease of adoption. The purpose of this research is to identify advanced Industry 4.0 technologies, operational excellence (OPEX) strategies and reconfigurable manufacturing system (RMS) practices. The study also computes their weights, as well as identifies and prioritizes the performance metrics for the same.

A thorough review of relevant articles was conducted to identify 28 OPEX strategies, RMS practices and advanced technologies, as well as the 17-performance metrics. The stepwise weight assessment ratio analysis approach was used to compute the weights of the selected practices, while the WASPAS approach was used to prioritize the performance metrics. While developing the framework, the industry expert’s expertise was incorporated in the form of their opinions for pairwise comparison.

According to the study findings, advanced Industry 4.0 technologies were the most prominent for improving organizational performance. As a result, integrating Industry 4.0 technologies with OPEX strategies can assist in improving the performance of manufacturing organizations. The prioritized performance metrics resulted in the production lead time ranking first and the use of advanced technologies ranking second. This emphasizes the significance of meeting dynamic customer needs on time while also improving quality with the help of advanced technologies.

The developed framework can help practitioners integrate OPEX strategies and advanced technologies into their organizations by adopting them in order of importance. Furthermore, the ranked performance metrics can assist managers and practitioners in evaluating the manufacturing system and, as a result, strategic planning for improvement.

According to the authors, this is a novel approach for integrating OPEX strategies with advanced Industry 4.0 technologies, and no comparable study has been found in the current literature.