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To review the state-of-the-art in smart remanufacturing, highlighting key elements of an Industry 4.0 (I4.0) future that supports circular economy (CE) principles and offer a conceptual framework and research agenda to accelerate digitalisation in this sector.

The Scopus, Web of Science and ScienceDirect databases and search terms “Industry 4.0”, “Internet of things”, “Smart manufacturing” and “Remanufacturing” were used to identify and select publications that had evidence of a relationship between those keywords. The 329 selected papers were reviewed with respect to the triple bottom line (economic, social and environmental). The study benefited from advanced text quantitative processing using NVivo software and a complete manual qualitative assessment.

Changes in product ownership models will affect the remanufacturing industry, with the growth of product-service-systems seen as an opportunity to re-circulate resources and create value. This is being supported by changes in society, user expectations and workforce attributes. Key to the success of remanufacturing in an I4.0 future is the uptake of existing and emerging digital technologies to shorten and strengthen links between product manufacturers, users and remanufacturers.

Remanufacturing is recognised as a key CE strategy, which in turn is an important research area for development in our society. This article is the first to study “smart remanufacturing” for the CE. Its uniqueness lies in its focus on the remanufacturing industry and the sustainable application of I4.0 enablers. The findings are used to create a framework that links to the research agenda needed to realise smart remanufacturing.

The objective of this study is to propose a sequence of implementation of the core characteristics of reconfigurability: modularity, integrability, diagnosability, adaptability and customization. For this purpose, the relationships among the core characteristics and Industry 4.0 technologies are analyzed as well as the impacts of one core characteristic on another.

This study presented tests and validated two hypothesized models based on the literature. This paper was based on a questionnaire survey. Portuguese manufacturing companies were the sampling frame. In total, 600 questionnaires were distributed and a total of 112 responses were eligible for statistical processing, representing a response rate of 18.7%. Structural equation modeling (SEM) was used to hypothesize the sequence of implementation of the core characteristics of reconfigurability.

The findings presented a roadmap to implement reconfigurability, which implies significant managerial contributions on how to make the transition from conventional to reconfigurable manufacturing systems (RMSs). This highlights the importance of the sequence of implementation of the core characteristics in order to make the most of each to achieve reconfigurability.

Implementing reconfigurability is crucial to manufacturing companies to respond to changes in production requirements and market fluctuations quickly. However, there is a gap between theory and practice in regard to achieve reconfigurability in existing manufacturing systems. This gap includes (1) understanding the type of relationships among the core characteristics of reconfigurability, (2) understanding the influence that one core characteristic has on another and (3) establishing a sequence of implementation for the core characteristics. This study makes a contribution to fill this gap in the research area.

The purpose of this paper is to investigate the current level of reconfigurability implementation and its impact on manufacturing systems’ operational performance empirically.

This study is based on a questionnaire survey. Statistical analysis procedures were adopted to accomplish its objectives, namely, clustering methods based on cluster centroids. An ANOVA analysis was used to test for cluster differences among the variables.

The results show that the manufacturing companies surveyed can be divided into three clusters, with different levels of reconfigurability implemented. The implementation of the core characteristics of reconfigurability depends on the product’s complexity and demand variability, in terms of volume and product mix, as these have an impact on the operational performance, in terms of quality, delivery and flexibility.

The data for this survey were collected from manufacturing companies based in Portugal. Therefore, the replication of this questionnaire in other countries is recommended for future research to confirm its findings.

The questionnaire developed could be used by managers to assess the level of reconfigurability of their production systems and for internal/external benchmarking. The findings may help managers to decide which core characteristics should be implemented in their manufacturing systems.

The majority of the research addressing performance issues in reconfigurable manufacturing systems has been applied to case studies. This research reports an empirical investigation using a questionnaire-based methodology to provide generalisable empirical evidence.

Special software in a CAD system can help a designer evaluate an assembly and redesign it for automation.

This research integrates maintenance planning and production scheduling from a green perspective to reduce the carbon footprint.

A mixed-integer nonlinear programming (MINLP) model is developed to study the relation between production makespan, energy consumption, maintenance actions and footprint, i.e. service level and sustainability measures. The speed scaling technique is used to control energy consumption, the capping policy is used to control CO2 footprint and preventive maintenance (PM) is used to keep the machine working in healthy conditions.

It was found that ignoring maintenance activities increases the schedule makespan by more than 21.80%, the total maintenance time required to keep the machine healthy by up to 75.33% and the CO2 footprint by 15%.

The proposed optimization model can simultaneously be used for maintenance planning, job scheduling and footprint minimization. Furthermore, it can be extended to consider other maintenance activities and production configurations, e.g. flow shop or job shop scheduling.

Maintenance planning, production scheduling and greenhouse gas (GHG) emissions are intertwined in the industry. The proposed model enhances the performance of the maintenance and production systems. Furthermore, it shows the value of conducting maintenance activities on the machine's availability and CO2 footprint.

This work contributes to the literature by combining maintenance planning, single-machine scheduling and environmental aspects in an integrated MINLP model. In addition, the model considers several practical features, such as machine-aging rate, speed scaling technique to control emissions, minimal repair (MR) and PM.

The purpose of this paper is to develop and test a design approach based on the investigation of the sensitivity of assembly systems to volume fluctuations as part of the selection process of alternative design solutions for scalable assembly systems on the basis of a real industrial case study.

A conceptual approach for the (re‐)design of a scalable assembly system is developed on the basis of an industrial case research using axiomatic design (AD) for the top level structuring of the framework incorporating useful methods and insights obtained from a thorough literature review and from previous research work.

The findings of this research are limited due to the focused nature of a case study based research. However, the obtained results encourage assuming its transferability to similar problems.

Significant research has been done in the design of assembly systems for high product variety, but the review of literature in this field still identifies many opportunities for future research. This paper responds to the clearly identified research need of a methodological guidance regarding the design of scalable assembly systems and offers a practically proven help to improve the efficiency of the design process and the quality of the design results.

This research aims to examine the relevant literature related to maintenance performance measurement in the manufacturing sector. In the process, innovative approaches and models utilized to measure and manage maintenance performance in manufacturing operational settings are classified and examined. Based on this investigation, future research directions and themes are identified.

A database of 251 peer‐reviewed publications, published during the last 30 years, was utilized for the purpose of this research. The published works included contributions from both practitioners and scholars.

This literature review‐based research revealed important themes related to evolution of maintenance performance management. These themes focus on the effective utilization of maintenance resources, information systems support, and human factor management. Based on this literature review, a conceptual framework, which traces the different operational and organizational facets of the evolution of maintenance performance management, is offered.

Based on the findings of this study, it is concluded that the area of maintenance performance and management is in need of more future systematic research efforts aimed at solidifying theoretical constructs and promoting the utilization of more practical applications.

Findings derived from this investigation have relevant manufacturing implications. In this context, understanding the different approaches to maintenance performance measurement and management, as utilized in manufacturing organizations, is critical to these organizations' performance improvement efforts.

Understanding the types and scopes of the different approaches and models utilized to manage and measure maintenance performance in manufacturing operational settings is important in light of the growing competitiveness of the manufacturing sector.

Advancements in responsive manufacturing have been supporting companies over the last few decades. However, manufacturers now operate in a context of continuous uncertainty. This research paper explores a mechanism where companies can “elastically” provision and deprovision their production capacity, to enable them in coping with repeated disruptions. Such a mechanism is facilitated by the imitability and substitutability of production resources.

An inductive study was conducted using Gioia methodology for this theory generation research. Respondents from 20 UK manufacturing companies across multiple industrial sectors reflected on their experience during COVID-19. Resource-based view and resource dependence theory were employed to analyse the manufacturers' use of internal and external production resources.

The study identifies elastic responses at four operational levels: production-line, factory, company and supply chain. Elastic responses that imposed variable-costs were particularly well-suited for coping with unforeseen disruptions. Further, the imitability and substitutability of manufacturers helped others produce alternate goods during the crisis.

While uniqueness of production capability helps manufacturers sustain competitive advantage against competitors during stable operations, imitability and substitutability are beneficial during a crisis. Successful manufacturing companies need to combine these two approaches to respond effectively to repeated disruptions in a context of ongoing uncertainties. The theoretical contribution is in characterising responsive manufacturing in terms of resource heterogeneity and resource homogeneity, with elastic resourcing as the underlying mechanism.

The findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.

We have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.

BA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.

There are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.