Joint optimisation of inspection maintenance and spare parts provisioning: a comparative study of inventory policies using simulation and survey data

The demand for industrial plant spare parts is driven, at least in part, by maintenance requirements. It is therefore important to jointly optimise planned maintenance and the associated spare parts inventory using the most appropriate maintenance and replenishment policies. In this simulation-based study, we address this challenge in the context of the random failure of parts in service and the replacement of defective parts at inspections of period T. Inspections are modelled using the delay-time concept. A number of simultaneous periodic review and continuous review replenishment policies are compared. A paper making plant provides a real context for the presentation of our ideas. We survey practitioners working with such plant to collect real data that inform the values of parameters in the models. Our simulation results indicate that a periodic review policy with ordering that is twice as frequent as inspection is cost optimal in the context of the plant that we study. For the purpose of comparison, we also present and discuss the characteristics of the various policies considered

Development of an optimization model to determine sampling levels

As the complexity of multi-component products increases the quality of these products becomes increasingly difficult to control. The first step to manufacturing a quality product is making sure that the components of the product meet specifications. Product quality can be controlled through sampling inspection of the components. Two models were developed in this research to determine the optimal sampling levels for incoming lots containing parts for production and assembly of multi-component systems. The main objective of the first model is to minimize the expected cost that is associated with a nonconforming item reaching assembly. In this model the time available for inspection is limited. The main objective in the second model is to minimize total cost, which includes the appraisal cost (inspection cost) and the cost associated with nonconformance reaching assembly. In this model the time available is not a constraint. The distribution of defects is assumed to follow the binomial distribution, and the distribution of accepting the lot with defects follows the hypergeometric distribution. In addition, the inspection is considered to be accurate and, if a nonconforming item is found in the inspected sample, the entire lot is rejected. An example is given with real world data and the results are discussed --Abstract, page iv

Multi-defect modelling of bridge deterioration using truncated inspection records

Bridge Management Systems (BMS) are decision support tools that have gained widespread use across the transportation infrastructure management industry. The Whole Life Cycle Cost (WLCC) modelling in a BMS is typically composed of two main components: a deterioration model and a decision model. An accurate deterioration model is fundamental to any quality decision output.There are examples of deterministic and stochastic models for predictive deterioration modelling in the literature, however the condition of a bridge in these models is considered as an ‘overall’ condition which is either the worst condition or some aggregation of all the defects present. This research proposes a predictive bridge deterioration model which computes deterioration profiles for several distinct deterioration mechanisms on a bridge.The predictive deterioration model is composed of multiple Markov Chains, estimated using a method of maximum likelihood applied to panel data. The data available for all the defects types at each inspection is incomplete. As such, the proposed method considers that only the most significant defects are recorded, and inference is required regarding the less severe defects. A portfolio of 9,726 masonry railway bridges, with an average of 2.47 inspections per bridge, in the United Kingdom is the case study considered

Maintenance Optimization and Inspection Planning of Wind Energy Assets: Models, Methods and Strategies

Designing cost-effective inspection and maintenance programmes for wind energy farms is a complex task involving a high degree of uncertainty due to diversity of assets and their corresponding damage mechanisms and failure modes, weather-dependent transport conditions, unpredictable spare parts demand, insufficient space or poor accessibility for maintenance and repair, limited availability of resources in terms of equipment and skilled manpower, etc. In recent years, maintenance optimization has attracted the attention of many researchers and practitioners from various sectors of the wind energy industry, including manufacturers, component suppliers, maintenance contractors and others. In this paper, we propose a conceptual classification framework for the available literature on maintenance policy optimization and inspection planning of wind energy systems and structures (turbines, foundations, power cables and electrical substations). The developed framework addresses a wide range of theoretical and practical issues, including the models, methods, and the strategies employed to optimise maintenance decisions and inspection procedures in wind farms. The literature published to date on the subject of this article is critically reviewed and several research gaps are identified. Moreover, the available studies are systematically classified using different criteria and some research directions of potential interest to operational researchers are highlighted

Modelling and simulation for the joint optimisation of inspection maintenance and spare parts inventory in multi-line production settings

A simulation methodology is developed to model the joint optimisation of preventive maintenance and spare parts inventory in multi-line settings. The multi-line machines are subject to failure, based on the delay-time concept, and a selection of policies are used for the replenishment of the machines’ critical component. Production lines of varied configurations are modelled and described in three principal chapters. Firstly, the optimisation of preventive maintenance for a multi-line production system is developed in the context of a case study. The policy proposed indicates that consecutive inspection with priority for failure repair is cost-optimal, which suggests a substantial maintenance cost reduction of 61% compared to the run-to-failure policy. The contribution of this study is first and foremost in narrowing the gap between the theory and practice of managing multi-line systems, and in particular, that the scenarios and policies considered have important economic and engineering implications. In a second study, spare parts provisioning for a single-line system is considered, given that the demand for industrial plant spare parts should be driven, at least in part, by maintenance requirements. A paper-making plant provides a real context, for which simulation models are developed to jointly optimise the planned maintenance and the associated spare part inventory. This challenge is addressed in the context of the failure of parts in service and the replacement of defective parts at inspections of period T, using the delay-time concept, and a selection of replenishment policies. The results indicate that a periodic review policy with replenishment twice as frequent as inspection is cost-optimal. Further discussions and sensitivity analysis give insights into the characteristics and features of the policies considered. Finally, in the third study, the joint optimisation of preventive maintenance and the associated spare parts inventory for a multi-line system is developed using an idealised context. It is found that a review policy with inspection as frequent as replenishment using just-in-time (JIT) ordering is cost-optimal, and also the lowest risk policy; it is associated with the lowest simultaneous machine downtime and low stock-out cost-rates. This is a significant contribution to the literature. An implication of the proposed methodology is that, where mathematical modelling is intractable, or the use of certain assumptions make them less practical, simulation modelling is an appropriate solution tool. Throughout this thesis, the long-run average cost per unit time or cost-rate is used as the optimality criterion. In other contexts, one may wish to use availability or reliability instead. To do so would not change the methodology that is presented here