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A method for the automatic selection of tools in a disassembly or assembly environment is described. The method uses a cluster graph to represent the product in a fashion suitable for the simple identification of part inter‐relationships within the product. This graphical representation of the product is then converted directly into a dynamic programming model. To this dynamic programming model cost data are added and the optimum tool selection path is produced.

The apparel industry in high wage countries can only be competitive globally by rationalizing its production process with automation. A particular stress is to be laid on the handling. Up to now, the development of new features has concentrated on the sewing process itself. Due to this, the correct feeding of the textile material defines a challenge to be solved. For feeding the textiles, the exact compliance of position and orientation is of considerable importance. Difficulties lie in tracking the edge of the material due to its defects, e.g. outgoing threads. This paper describes a low‐cost infrared sensor system for contour tracking and detection of edge defects. Statistical analysis of the results obtained from 20 different fabrics is provided.

Sustainability is an area of increasing interest for industry and its stakeholders, and some companies now aspire to address sustainability issues (e.g. carbon emissions) at strategic and operational levels. As companies are exploring the issues, they attempt to embed sustainability in their planning and management systems. It is at this point that the domains of environmental concern and performance management meet. The research questions explored in this paper are: what is the size of environmental performance variation? What are the challenges for sustainability performance management in practice?

First, interviews in manufacturing companies were conducted to understand the size of environmental performance variation. Subsequently, a survey, interviews and a workshop were conducted with ten organisations to gain insight in environmental performance management in companies.

It was observed that, across three sectors, environmental performance between manufacturing plants differed up to 500 per cent between worst and best performing factories which make similar products using similar technology, all in well-run companies which have environmental management programmes in place. This means that learning within the company between different sites is important but can be difficult. Some initial success stories observed include a quid-pro-quo approach between factory sites (teach-learn-do-teach) and dedicated individuals (champions) in factories who strive to make year-on-year efficiency improvements.

The paper gives insights in the size of environmental performance variation, self-reported by internal company specialists in sustainable manufacturing, and sustainability performance management in practice.

Following an increasing interest in the area that merges digital/I4.0 technologies and business models (BMs), which led to a proliferation of articles in this domain, the purpose of this article is to systematize this body of literature by means of a structured literature review.

After a careful selection of articles, we carried out the analysis with the support of bibliometric techniques, using the bibliographic coupling approach complemented with factor analysis and the content analysis of articles.

The results of the literature review analysis allow us to organize the literature around four main research streams, namely digital technologies and business model innovation, digital strategy and BMs, digital platforms and BMs, and IoT, servitization and BMs. On such a basis, we outline gaps and provide promising avenues for further research in this research area.

This study has implications for academics in terms of conceptualization of relevant constructs, integration of two streams of research and specific technologies whose relationship with the BM still deserves attention.

This study has implications also for managers, who may take advantage of the description of some BM archetypes driven by digital/I4.0 technologies and also appreciate the relevance of taking a strategic approach, with a particular focus on the BM, toward the use of digital technologies.

This study merges two relevant streams of research in an attempt to see how they have developed synergically and what potentials their merge could offer for future research.

The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of data generated from different types of manufacturing operations. The present study, therefore, aims to conduct a systematic and bibliometric-based review in the applications of machine learning (ML) techniques for sustainable manufacturing (SM).

In the present study, the authors use a bibliometric review approach that is focused on the statistical analysis of published scientific documents with an unbiased objective of the current status and future research potential of ML applications in sustainable manufacturing.

The present study highlights how manufacturing industries can benefit from ML techniques when applied to address SM issues. Based on the findings, a ML-SM framework is proposed. The framework will be helpful to researchers, policymakers and practitioners to provide guidelines on the successful management of SM practices.

A comprehensive and bibliometric review of opportunities for ML techniques in SM with a framework is still limited in the available literature. This study addresses the bibliometric analysis of ML applications in SM, which further adds to the originality.

The aim of the study is to explore the possible practical impact of big data/business intelligence and Internet of Things on the purchasing process of premium automotive manufacturers, and to evaluate its theoretical impact with a transaction cost economics approach.

An exploratory multiple-case study was carried out, using qualitative content analysis and cross-case synthesis.

Collaborative platforms and a new purchaser role were found to impact the entire process. In the strategic purchasing 4.0 process, co-creation of specifications, automated prequalification, and parameter-based negotiations are some expected changes. The operative purchasing 4.0 process is shaped by, for example, interactive call-offs. Transaction cost is expected to decrease by reduced uncertainty and supplier specificity, as well as by lowered information search, negotiation, and monitoring costs.

The description of a potential purchasing 4.0 process for premium automotive manufacturers is given.

Premium automotive manufacturers can develop strategies to push the existing standards of purchasing. Suppliers can create scenarios to allow for future compliance at the purchasing–sales interface.

New technologies' effects on the workforce are considered.

No identified study focused on the impact of Industry 4.0 technologies on the purchasing process of premium automotive manufacturers.

This paper aims to present a one-shot gesture recognition approach which can be a high-efficient communication channel in human–robot collaboration systems.

This paper applies dynamic time warping (DTW) to align two gesture sequences in temporal domain with a novel frame-wise distance measure which matches local features in spatial domain. Furthermore, a novel and robust bidirectional attention region extraction method is proposed to retain information in both movement and hold phase of a gesture.

The proposed approach is capable of providing efficient one-shot gesture recognition without elaborately designed features. The experiments on a social robot (JiaJia) demonstrate that the proposed approach can be used in a human–robot collaboration system flexibly.

According to previous literature, there are no similar solutions that can achieve an efficient gesture recognition with simple local feature descriptor and combine the advantages of local features with DTW.

The emergence the fourth industrial revolution, known as well as industry 4.0, and its applications in the manufacturing sector ushered a new era for the business entities. It not only promises enhancement in operational efficiency but also magnify sustainable operations practices. This current paper provides a thorough bibliometric and network analysis of more than 600 articles highlighting the benefits in favor of the sustainability dimension in the industry 4.0 paradigm.

The analysis begins by identifying over 1,000 published articles in Scopus, which were then refined to works of proven influence and those authored by influential researchers. Using rigorous bibliometric software, established and emergent research clusters were identified for intellectual network analysis, identification of key research topics, interrelations and collaboration patterns.

This bibliometric analysis of the field helps graphically to illustrate the publications evolution over time and identify areas of current research interests and potential directions for future research. The findings provide a robust roadmap for mapping the research territory in the field of industry 4.0 and sustainability.

As the literature on sustainability and industry 4.0 expands, reviews capable of systematizing the main trends and topics of this research field are relevant.

With the increasing pressures towards global sustainability and the transition to Industry 4.0 (I4.0), the collaboration between firms and other key stakeholders is essential. Value is no longer created by firms acting autonomously, but rather by firms acting together with external parties. Therefore, the aim of this study is to explore the potential contribution of capability providers to a Sustainable I4.0 Environment as an additional perspective regarding the management decisions of a smart and sustainable business model (SSBM) transformation of big corporations.

An in-depth qualitative case study of Futuryng INC., which is a company based in Silicon Valley, New York and Italy, is presented and analysed through interviews, secondary sources and using a triangulation approach. The company is a Connected Technologies Ecosystem, which acts as a provider of technology building blocks (capability) able to design and release end-to-end Information Technologies–Internet of Things–Operational Technologies (IT-IoT-OT) Solutions.

From the case study, the authors determine that the success of big corporations' SSBM transformation requires a Sustainable I4.0 Environment approach where capability providers play a relevant role and act as enablers. Then, the authors develop a framework by adopting an actor perspective, called the Sustainable I4.0 Environment, highlighting the contribution of the capability provider in the sustainable I4.0 business model transformation of a big corporation.

The authors’ analysis clarifies that the successful execution of a sustainable I4.0 business model transformation requires integrated thinking for management decisions and a co-creation approach with capability providers, along with an open innovation process.

In the analysis of I4.0 and sustainability issues, previous studies only focus on implementing firms and view the environment merely as a background in which act forces of sustainability and I4.0. A comprehensive overview of the Sustainable I4.0 Environment, which considers actors and their contribution, is lacking. By integrating the literature review with the case study, the authors’ research proposes a comprehensive framework to guide the decision process of transformation from a traditional business model (TBM) to an SSBM and considers one of the key actors involved, the capability providers.