Research on scheduling problems is an evergreen challenge for industrial engineers. The growth of digital technologies opens the possibility to collect and analyze great amount of field data in real-time, representing a precious opportunity for an improved scheduling activity. Thus, scheduling under uncertain scenarios may benefit from the possibility to grasp the current operating conditions of the industrial equipment in real-time and take them into account when elaborating the best production schedules. To this end, the article proposes a proof-of-concept of a simheuristics framework for robust scheduling applied to a Flow Shop Scheduling Problem. The framework is composed of genetic algorithms for schedule optimization and discrete event simulation and is synchronized with the field through a Digital Twin (DT) that employs an Equipment Prognostics and Health Management (EPHM) module. The contribution of the EPHM module inside the DT-based framework is the real time computation of the failure probability of the equipment, with data-driven statistical models that take sensor data from the field as input. The viability of the framework is demonstrated in a flow shop application in a laboratory environment.

Despite the huge body of academic literature on inventory management of maintenance spare parts, few companies seem to deliberately use the proper approaches and tools for a factual and quantitative assessment. Detaining or not stocks of a spare item, deciding upon the right level of inventory, forecasting its sporadic consumption are just some of the evidences of the complexity and criticality underlying the daily decisions the management of a company has to undertake. The objective of the paper is to provide a stepwise decision-making path in order to orienteer an industrial manager on how to pragmatically handle the management of maintenance spare parts in a company. The framework is structured into five sequential steps: part coding, part classification, part demand forecasting, stock management policy and policy test and validation. Its applicability is demonstrated by making use of a real business case where it has been successfully adopted.

The advanced use of the Information and Communication Technologies is evolving the way that systems are managed and maintained. A great number of techniques and methods have emerged in the light of these advances allowing to have an accurate and knowledge about the systems’ condition evolution and remaining useful life. The advances are recognised as outcomes of an innovative discipline, nowadays discussed under the term of Prognostics and Health Management (PHM). In order to analyse how maintenance will change using PHM, a conceptual model is proposed built upon three views. The model highlights: (i) how PHM may impact the definition of maintenance policies; (ii) how PHM fits within the condition-based maintenance; and (iii) how PHM can be integrated into reliability-centred maintenance programmes. The conceptual model is the research finding of this review note and helps to discuss the role of PHM in advanced maintenance systems.

Purpose: – Spare parts management plays a relevant role for equipment-intensive companies. An important step of such process is the spare parts classification, enabling properly managing different items by taking into account their peculiarities. The purpose of this paper is to review the state of the art of classification of spare parts for manufacturing equipment by presenting an extensive literature analysis followed by an industrial assessment, with the final aim to identify eventual discrepancies. Design/methodology/approach: – Not only is the attention put on the literature about the subject, but also on an on-field analysis, that is presented comprehending an extensive survey and two in-depth exploratory case studies. The copper mining sector was chosen being representative for the case of capital intensive plants where the cost of maintenance has relevant weight on the total operating cost. Findings: – The paper highlights the status of the scientific literature on spare parts classification by showing the current situation in the real industrial world. The paper depicts the existing barriers that leave gaps between theory and real practice for the application of an effective multi-criteria spare parts classification. Originality/value: – The paper provides a review of the theory on spare parts classification methods and criteria, as well as empirical evidences especially for what concern current situation and barriers for an effective implementation in the industrial environment. The paper should be of interest to both academics and practitioners, since it provides original insights on the discrepancies between scientific and industrial world.