Asset-intensive industries, such as the construction industry, have experienced major catastrophes that have led to significant operational disruptions. Physical asset failure has been the primary cause of these disruptions. Therefore, implementing proper asset management plans, including continuity plans, is crucial for the business continuity of companies active in these industries. However, companies often face severe resource limitations when implementing these plans for all of their physical assets. Therefore, those critical physical assets that are vital for providing their key products should be identified. Moreover, sustainability and resilience are inseparable parts of organizations’ strategies, including strategic asset management plans. Therefore, any proposed ranking methodology for physical asset prioritization should encompass sustainability and resilience measures to ensure its practicality. This paper proposes a novel framework for physical asset criticality analysis based on the so-called business impact analysis to ensure the continuity of providing products/services through the continuity of physical assets. A hybrid fuzzy BWM-TOPSIS method is first applied to identify the key products. Then, a hybrid fuzzy DEMATEL-Bayesian network is applied based on proper sustainability and resilience factors to determine the critical physical assets, while interdependencies among these factors are well captured. The normalized expected asset criticality index is defined to guide managers in taking appropriate directions while developing asset management plans. A case study of a gas company is provided to show the applicability of the proposed decision model. The data needed for each step of the framework is gathered through experts’ judgments, historical data available on the sites, or quantitative risk assessment scenarios.

The objective of this paper is to apply the activity-based costing (ABC) approach together with traditional costing (TC) for parts costing in flexible manufacturing systems (FMS) with the A(2) level of automation. We propose a new model for the implementation of ABC using the product cost tree concept. First, the required resources and activities for each part are recorded, and then their costs are calculated using the appropriate cost formulae. This model was applied in a forging industry. A comparison and analysis between ABC and TC was then carried out based on the computational results obtained from the case study. The results indicate that the ABC outputs are more reliable than the TC outputs, and thus the ABC approach is a more acceptable tool for parts costing in FMS.