Search

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Digital technologies are becoming more pervasive and industrial companies are exploiting them to enhance the potentialities related to Prognostics and Health Management (PHM). Indeed, PHM allows to evaluate the health state of the physical assets as well as to predict their future behaviour. To be effective in developing PHM programs, the most critical assets should be identified so to direct modelling efforts. Several techniques could be adopted to evaluate asset criticality; in industrial practice, criticality analysis is amongst the most utilised. Despite the advancement of artificial intelligence for data analysis and predictions, the criticality analysis, which is built upon both quantitative and qualitative data, has not been improved accordingly. It is the goal of this work to propose an ontological formalisation of a multi-attribute criticality analysis in order to i) fix the semantics behind the terms involved in the analysis, ii) standardize and uniform the way criticality analysis is performed, and iii) take advantage of the reasoning capabilities to automatically evaluate asset criticality and associate a suitable maintenance strategy. The developed ontology, called MOCA, is tested in a food company featuring a global footprint. The application shows that MOCA can accomplish the prefixed goals; specifically, high priority assets towards which direct PHM programs are identified. In the long run, ontologies could serve as a unique knowledge base that integrate multiple data and information across facilities in a consistent way. As such, they will enable advanced analytics to take place, allowing to move towards cognitive Cyber Physical Systems that enhance business performance for companies spread worldwide. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This research focuses on responsiveness in high variety manufacturing environments. To achieve it, the article proposes to develop Dynamic Response Capabilities (DRCs) of the manufacturing system defined as the abilities to readjust the planned operating parameters of workload, capacity, and lead time, in the wake of disturbances. To inform their development, built on the Workload Control theory, a routine-based framework is proposed. The framework supports an integrated approach for the implementation of adaptive decision-making routines for workload, capacity, and lead time readjustments at different stages in the order fulfilment process. Findings from two empirical cases show the appropriateness of the framework to develop and utilise DRCs in different settings of disturbances. Results of a simulation study, with one of the case companies, also shows the effectiveness of the framework to drive performance improvements in presence of recurring disturbances leading to demand variability. [ABSTRACT FROM AUTHOR]

Purpose - The customer enquiry management (CEM) process is of strategic importance in engineer-to-order contexts but existing literature does not adequately describe how firms support delivery date setting and order acceptance decisions in practice. This paper seeks to explore how and why the CEM process varies between companies in the capital goods sector, thereby taking a contingency theory approach. Design/methodology/approach - Multi-case study research involving 18 Italian capital goods manufacturers in four industrial sectors. Face-to-face interviews with senior representatives have been conducted. Companies have been grouped into five clusters, based on similarities in their CEM decision-making modes, to aid analysis. Findings - Three contingency factors were found to be particularly relevant in determining CEM modes: degree of product customization, flexibility of the production system, and uncertainty of the context. These factors affect the choice of specific CEM decision-making modes. However, a high level of cross-functional coordination and formalization of the process were found to constitute best practices whatever the contingency factors. Research limitations/implications - The research focuses on companies belonging to the Italian capital goods sector - findings may differ in other countries and sectors. Practical implications - The results indicate that all firms, including small and medium-sized companies, should implement high levels of cross-functional coordination and formalization in their CEM practices, in order to improve their performance. For other aspects of the CEM process, including supplier and subcontractor monitoring, the company context will indicate whether these aspects are required, according to a need of matching the approach to CEM with specific sets of contingency factors. Originality/value - This paper provides a rare insight into the CEM processes found in practice. Keywords Customer service management, Customization, Delivery dates, Italy Paper type Research paper [ABSTRACT FROM AUTHOR]

This paper tackles the problem of scheduling in the assembly of SMT electronic boards. In particular, it focuses on a new scheduling method developed within the framework of an industry-university joint research project. The scheduling system aims at minimizing the makespan; this goal is achieved by reducing setup times and idle times of the machines. As an example, the outcome of a test carried out on a production mix made up of 10 board types is presented and analyzed in a summarized form. [ABSTRACT FROM AUTHOR]