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This paper aims to provide a service-based integrated prototype framework for the design of reusable modular assembly systems (RMAS) incorporating reusability of equipment into the process. It extends AutomationML (AML) developments for an engineering data exchange to integrate and standardize the data formats that support the design of RMAS.

The approach provides a set of systematic procedures and support tools for the design of RMAS. This includes enhanced domain knowledge models that facilitate the interpretation and integration of information across the design phases.

The inclusion of reusability aspects in the design phase improves the sustainability of future assembly systems, by ensuring equipment use until its end-of-life. Moreover, the integrated support tools reduce the design time, while improving the quality/performance of the system design solution, as it enables the exploration of a larger solution space. This will result in a better response to dynamic and rapidly changing system requirements.

This work provides a sustainable approach for the design of modular assembly systems (MAS), which will ensure better resource utilization. Additionally, the standardization of the data and the support of low cost tools is expected to benefit industrial companies, particularly the small- and medium-sized enterprises.

This approach offers a service-based platform which uses production data to incorporate reusability aspects into the design process of modular assembly system. Moreover, it provides a framework for modular assembly system design by extending the current design processes and interactions between stakeholders. To support this, a standardized method for information representation and exchange across the several phases of the RMAS design activity is briefly illustrated with an industrial case study.

The development of reconfigurable modular production systems is one of the crucial factors for manufacturers to sustain their competitive advantage in areas such as precision assembly. To ensure the effective and cost efficient configuration and successive reconfigurations it is of critical importance to involve all stakeholders in the decision‐making process. The reported research is targeting the development of an integrated Web‐enabled decision‐making environment that supports some of the key assembly system engineering stages from user requirement specification to system implementation. The focus is on the design of assembly workstations based on detailed process requirements with a target of developing highly efficient and cost‐effective solutions. The paper presents an application framework for collaborative distributed design supported by domain ontologies and is illustrated using an industrial case study.

One of the key factors for success in assembly automation at present is the ability of system integrators to deliver more reliable and customised systems within shorter periods of time. Despite the active research in the development of distributed engineering support systems, there is a clear need for practical methods and tools to support the interactions between different stakeholders at the early product and assembly system design stages. This paper reports on the development of assembly process and equipment data models using context free grammars. The models enable a web‐based decision‐making for formation of assembly workstations using distributed linguistic approach.

Current major roadmapping efforts have all clearly underlined that true industrial sustainability will require far higher levels of systems' autonomy and adaptability. In accordance with these recommendations, the Evolvable Assembly Systems (EAS) has aimed at developing such technological solutions and support mechanisms. Since its inception in 2002 as a next generation of production systems, the concept is being further developed and tested to emerge as a production system paradigm. The essence of evolvability resides not only in the ability of system components to adapt to the changing conditions of operation, but also to assist in the evolution of these components in time. Characteristically, Evolvable systems have distributed control, and are composed of intelligent modules with embedded control. To assist the development and life cycle, a methodological framework is being developed. After validating the process‐oriented approach (EC FP6 EUPASS project), EAS now tackles its current major challenge (FP7 IDEAS project) in proving that factory responsiveness can be improved using lighter multi‐agent technology running on EAS modules (modules with embedded control). The purpose of this paper is to detail the particular developments within the IDEAS project, which include the first self re‐configuring system demonstration and a new mechatronic architecture.

The paper covers the development of a plug & produce system for FESTO AG. The work covers the background methodology and details its constituents: control system, architecture, design methodology, and modularity. Specific detail is reserved for the configuration approach which integrates several tools, and the commercially available control boards. The latter have been specifically developed for distributed control applications.

The paper details probably the first self‐configuring assembly system at shop‐floor level. This is one of the very first industrial plug & produce systems, in which equipment may be added/removed with no programming effort at all.

The paper reports the findings and development carried out within the framework of a single project. It also clarifies that the solution is not a general panacea for all the issues within assembly.

The implications are quite large as the work proves the validity of an approach that could change our way of designing and building assembly systems. In the words of an industrial partner, this is “a new way of engineering assembly systems”.

Should this approach be used in industry then the implications could be huge. It would, for example, mean that new services are created, whereby assembly system modules are leased to users through a network of depots, rather than bought at a high cost. The system modules also have a far longer lifespan, implying very good ecological solutions.

The highly original paper describes what is probably one of the very first projects to show that distributed control at shop‐floor level is viable and technologically feasible.

To present a methodology for requirements specification for assembly system reconfiguration.

Industrial needs were analysed through a series of interviews with personnel involved in the design and sales process. This was then compared to reported research in literature and a new method has been derived and demonstrated.

An improved methodology for requirements specification leading to more efficient design and deployment of reconfigurable assembly systems.

Provides a structured mechanism for performing requirements specification tasks that are currently done on an ad hoc basis.

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.

To use the theory of planned behavior (TPB) as a theoretical framework to explore in depth the range of beliefs held by consumers about internet shopping in general and internet grocery shopping in particular.

Seven focus group interviews, four in the United Kingdom and three in Denmark, were conducted among consumers with different degrees of experience with internet grocery shopping. This diversification of respondents was chosen to capture a broad range of the consumer beliefs that predict intentions to buy groceries online or not. The TPB framework was used to construct the interview guide that was followed in all focus groups.

An unexpected result of the explorative study was that the seven groups consisting of more or less experienced internet shoppers differed only little in their pool of beliefs (outcome and control beliefs). Beliefs about internet grocery shopping, positive as well as negative, were remarkably congruent across groups. In the minds of consumers, internet grocery shopping is an advantage compared with conventional grocery shopping in terms of convenience, product range and price. Disadvantages, which could act as mental barriers, are, for instance, the risk of receiving inferior quality groceries and the loss of the recreational aspect of grocery shopping.

An important potential limitation of this research is the choice of focus groups as research methodology, which can prevent the elicitation of certain types of beliefs. If important beliefs concern issues of a more sensitive, personal character they are not likely to be mentioned in a focus group. Another limitation is the explorative nature of the research, which makes it impossible to attach weights to the importance of the elicited beliefs in predicting internet shopping behavior.

The findings could be used to direct attention to consumer beliefs about internet grocery shopping which have the potential of acting as barriers to this line of e‐commerce.

To shed some light on the role of consumers in an underperforming and understudied branch of internet retailing. Barriers in the consumers' minds to shop for groceries online are identified using an established theoretical framework.