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Industrial equipment/machinery is an important element of manufacturing. They are used for producing objects that people need for everyday use. Therefore, there is a challenge to adopt effective maintenance strategies to keep them well-functioning and well-maintained in production lines. This will save energy and materials and contribute genuinely to the circular economy and creating value. Remanufacturing or refurbishment is one of the strategies to extend life of such industrial equipment. The paper presents an initial framework of cost estimation model based on combination of activity-based costing (ABC) and human expertise to assist the decision-making on best life extension strategy (e.g. remanufacturing, refurbishment, repair) for industrial equipment. Firstly, ABC cost model is developed to calculate cost of life extension strategy to be used as a benchmark strategy. Next, expert opinions are employed to modify data of benchmark strategy, which is then used to estimate costs of other life extension strategies. The developed cost model has been implemented in VBA-based Excel® platform. A case study with application examples has been used to demonstrate the results of the initial cost model developed and its applicability in estimating and analysing cost of applying life extension strategy for industrial equipment. Finally, conclusions on the developed cost model have been reported.

Today, engineering science and information technologies have given us powerful computational tools to support production planning and inventory control. In history, the ABC classification is usually used for inventory items aggregation because the number of inventory items is so large that it is not computationally feasible to set stock and service control guidelines for each individual item. A fundamental principle in ABC classification is that, ranking all inventory items with respect to a notion of profit based on historical transactions.The difficulty is that the profit of one item not only comes from its own sales, but also from its influence on the sales of other items, that is, the 'cross selling effect'. In this paper a new algorithm of inventory classification based on the association rules is presented. By using the Support-Confidence framework the consideration of cross-selling effect is introduced to generate a new criterion that is then used to rank inventory items. A numeral example is used to explain the new algorithm and empirical experiments are implemented to evaluate its effectiveness and utility.

Highlights • The dynamic lot-sizing problem is highly complex and very important for the planning systems of manufacturing enterprises in time-varying environment. • We propose an extension model of the dynamic multi-product lot-sizing problem considering time-varying production setup cost and with dual constraints on dynamic capacities and resource limits. This will make the model more consistent with the actual situation. • Comparative experiments on synthesized problem instances were conducted by using the AMPL/CPLEX solver. It can solve linear, nonlinear and plastic mathematical programming problems often encountered in the optimization process. • The new model is efficient on finding solutions with high qualities and the maximum size of test problems can be more than 500 products. High qualities and fast solution can help with the planning of production cycles and batches in the factory. Abstract The dynamic lot-sizing problem is highly complex and very important for the planning systems of manufacturing enterprises in time-varying environment, where production factors such as the production setup costs, unit storage costs, and production capacities may constantly rise or fall in different planning periods over the entire planning horizon. This paper proposed an extension model of the dynamic multi-product lot-sizing problem considering time-varying production setup cost and with dual constraints on dynamic capacities and resource limits, which carters for the actual situation of modern production and manufacturing systems in time-varying environments. Comparative experiments on synthesized problem instances were conducted by using the AMPL/CPLEX solver, which showed that the new model is efficiently on finding solutions with high qualities and the maximum size of test problems can be more than 500 products. [ABSTRACT FROM AUTHOR]