Nowadays, manufacturing firms are dealing with the unpredictability of market requirements and the frequent changes induced by technological innovation. For this reason, firms are more and more addressing the need to be responsive at an affordable cost. To do so, they are required to develop a capability called reconfigurability. This paper is a review of the existing literature because the current need makes interesting to reflect on the state of the art of reconfigurability as a concept. This reflection has led to focus on reconfigurability characteristics for both their relevance and their relationships with managerial decisions in manufacturing. To this end, a framework has been proposed. It is based on system lifecycle and production levels. These two elements have been deduced from literature and identified as relevant dimensions for decision-making.

Nowadays, manufacturing firms need the reconfigurability capability to be responsive in the current context characterised by unpredictable and frequent market changes and the reduction of product life cycle. Despite the relevance of the subject, a challenge for practitioners is the development of a strategy aimed to increase the level of reconfigurability with long-term goals of customisation and responsiveness. Moreover, traditional manufacturing paradigms are disrupted by the transformation of manufacturing systems in cyber-physical systems (CPS), thus introducing innovative means also to increase the level of reconfigurability in manufacturing systems. This study investigates how the technologies underlying CPS support the reconfigurability capability along system life cycle. Thus the technologies underlying CPS are classified into seven categories and it is shown how they enable the sequence of utilisation of the reconfigurability characteristics (modularity, integrability, diagnosability, scalability, convertibility and customisation) along the system life cycle. The results of the study can guide practitioners in developing reconfigurability as a strategic capability. Moreover, different directions for future research can be considered, as discussed in the conclusion.

Purpose: The purpose of this work is to investigate industrial asset management (AM) in manufacturing. After depicting gaps for AM in this sector, the role of information as a key dimension is considered to realise a summary of challenges and advices for future development.Design/methodology/approach: The work is grounded on an extensive systematic literature review. Considering the eligible documents, descriptive statistics are provided and a content analysis is performed, both based on a sector-independent normative-based framework of analysis.Findings: AM principles, organisation and information are the dimensions defined to group ten areas of interest for AM in manufacturing. Information is the major concern for an effective AM implementation. Moreover, Internet of Things and big data management and analytics, as well as data modelling and ontology engineering, are the major technologies envisioned to advance the implementation of AM in manufacturing.Research limitations/implications: The identified challenges and advices for future development may serve to stimulate further research on AM in manufacturing, with special focus on information and data management. The sector-independent normative-based framework may also enable to analyse AM in different contexts of application, thus favouring cross-sectorial comparisons.Originality/value: Industries with higher operational risk, like Oil&Gas and infrastructure, are advanced in AM, while others, like some in manufacturing, are laggard in this respect. This literature review is the first of a kind addressing AM in manufacturing and depicts the state-of-the-art to pave the way for future research and development.

The current uncertain and volatile business context is challenging firms worldwide, leading to the need to be responsive at a competitive cost. This trend is so substantial that it even affects industries traditionally competing in rather stable contexts, such as the process industry. Although the process industry includes multiple sectors with different technologies and processes, these share several aspects that make the industry as a whole distinctive to the discrete manufacturing industry. Based on a literature review, this study identifies and describes trends leading the process industry to the need for responsiveness, corresponding solutions to accommodate the need, and related challenges hindering the industrialization and diffusion of solutions in this industry. This study shows that trends, such as the uncertainty and volatility of market requirements, are challenging the process industry to develop reconfigurability solutions across multiple production levels. The development of reconfigurability solutions is hindered by modularity, integrability, co-ordination and collaboration challenges.

Maintenance is evolving due to the double-sided influence of the Asset Management paradigm and digitalization. In this evolution, assessing the maintenance management process status in terms of process completeness, information and data completeness and integration is paramount to boost reliable data-driven decision-making. Grounding on Design Science Research, a methodology is realized to favour the comparison of two data models, a reference one and a company-specific one, used as a means to evaluate the process status. In particular, the methodology embeds a reference data model for the maintenance management process. Both methodology and data model are artefacts tested and refined during action research in an automotive company willing to improve the maintenance management process. The application of both artefacts demonstrates that the company is facilitated in planning improvement actions for various time horizons to foster a modern maintenance practice whose decision-making is more data-driven.