Simulation based optimization of joint maintenance and inventory for multi-components manufacturing systems

Maintenance and spare parts management are interrelated and the literature shows the significance of optimizing them jointly. Simulation is an efficient tool in modeling such a complex and stochastic problem. In this paper, we optimize preventive maintenance and spare provision policy under continuous review in a non-identical multi-component manufacturing system through a combined discrete event and continuous simulation model coupled with an optimization engine. The study shows that production dynamics and labor availability have a significant impact on maintenance performance. Optimization results of Simulated Annealing, Hill Climb and Random solutions are compared. The experiments show that Simulated annealing achieved the best results although the computation time was relatively high. Investigating multi-objective optimization might provide interesting results as well as more flexibility to the decision maker

Analisis Availabilitas dengan Mempertimbangkan Inventori Spare part dan Penyangga Menggunakan Pendekatan Simulasi (Studi Kasus: PT Petrowidada)

PT Petrowidada merupakan satu-satunya perusahaan yang memproduksi Pythalic Anhydride di Indonesia. Konsumen PT Petrowidada mencakup 45 konsumen yang terdiri atas perusahaan cat dan plastik domestik maupun manca negara. Kapasitas produksi PT Petrowidada pada saat ini adalah 70000 MTPY atau kurang lebih sebanyak 240 Ton per hari. Pada saat ini, kapasitas produksi pada Pabrik PA PT Petrowidada berkurang, hal ini disebabkan karena availabilitas produksi yang menurun. Availabilitas produksi ini dipengaruhi oleh availabilitas spare part pada PT Petrowidada. Availabilitas juga dapat mempengaruhi calendar day. Calendar day adalah salah satu parameter utama dalam proses produksi karena dapat mempengaruhi customer service level perusahaan. Untuk melakukan efisiensi calendar day, dapat dilakukan dengan mengadakan inventori penyangga pada awal periode produksi. Inventori penyangga dapat mengatasi permasalahan starving dan blocking pada saat terjadi down time. Berdasarkan permasalahan tersebut, maka pada penelitian ini akan dilakukan analisis availabilitas dengan mempertimbangkan inventori spare part dan inventori penyangga. Metode yang digunakan dalam penelitian ini adalah metode simulasi sistem diskrit karena simulasi sistem diskrit dapat mengakomodasi perilaku acak dan ketergantungan antar variabel. ============================================================================================================ PT Petrowidada is the only company producing Pythalic Anhydride in Indonesia. The customers of PT Petrowidada include 45 companies consisting of domestic and foreign paints and plastics companies. PT Petrowidada's current production is 70.000 MTPY or approximately 240 Ton per day. At present, the production capacity of PT Petrowidada PA factory is decreased due to decreased production availability. Availability of this production is influenced by the availability of spare parts at PT Petrowidada. Availability can also affect calendar days. The calendar days is one of the main parameters in the production process as it may affect the level of customer service of the company. To perform efficiency of the calendar day, it can be done by creating the buffer inventory at the beginning of the production period. Buffer inventory can overcome starvation and blocking problems in the event of down time. Based on these cases, in this research will be analyzed the availability by considering inventory spare part and inventory buffer. The method used in this research is discrete event simulation because this method is able to accommodate the system complexity

A novel approach for modelling complex maintenance systems using discrete event simulation

Existing approaches for modelling maintenance rely on oversimplified assumptions which prevent them from reflecting the complexity found in industrial systems. In this paper, we propose a novel approach that enables the modelling of non-identical multi-unit systems without restrictive assumptions on the number of units or their maintenance characteristics. Modelling complex interactions between maintenance strategies and their effects on assets in the system is achieved by accessing event queues in Discrete Event Simulation (DES). The approach utilises the wide success DES has achieved in manufacturing by allowing integration with models that are closely related to maintenance such as production and spare parts systems. Additional advantages of using DES include rapid modelling and visual interactive simulation. The proposed approach is demonstrated in a simulation based optimisation study of a published case. The current research is one of the first to optimise maintenance strategies simultaneously with their parameters while considering production dynamics and spare parts management. The findings of this research provide insights for non-conflicting objectives in maintenance systems. In addition, the proposed approach can be used to facilitate the simulation and optimisation of industrial maintenance systems

State of the art in simulation-based optimisation for maintenance systems

Recently, more attention has been directed towards improving and optimising maintenance in manufacturing systems using simulation. This paper aims to report the state of the art in simulation-based optimisation of maintenance by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. The authors investigate application areas and published real case studies as well as researched maintenance strategies and policies. Much of the research in this area is focusing on preventive maintenance and optimising preventive maintenance frequency that will lead to the minimum cost. Discrete event simulation was the most reported technique to model maintenance systems whereas modern optimisation methods such as Genetic Algorithms was the most reported optimisation method in the literature. On this basis, the paper identifies the current gaps and discusses future prospects. Further research can be done to develop a framework that guides the experimenting process with different maintenance strategies and policies. More real case studies can be conducted on multi-objective optimisation and condition based maintenance especially in a production context

Simulation-based optimisation of complex maintenance systems

There is a potential as well as a growing interest amongst researchers to utilise simulation in optimising maintenance systems. The state of the art in simulation-based optimisation of maintenance was established by systematically classifying the published literature and outlining main trends in modelling and optimising maintenance systems. In general, approaches to optimise maintenance varied significantly in the literature. Overall, these studies highlight the need for a framework that unifies the approach to optimising maintenance systems. Framework requirements were established through two main sources of published research. Surveys on maintenance simulation optimisation were examined to document comments on the approaches authors follow while optimising maintenance systems. In addition, advanced and future maintenance strategies were documented to ensure it can be accommodated in the proposed framework. The proposed framework was developed using a standard flowchart tool due to its familiarity and ability to depict decision structures clearly. It provides a systematic methodology that details the steps required to connect the simulation model to an optimisation engine. Not only it provides guidance in terms of formulating the optimal problem for the maintenance system at hand but it also provides support and assistance in defining the optimisation scope and investigating applicable maintenance strategies. Additionally, it considers current issues relating to maintenance systems both in research and in practice such as uncertainty, complexity and multi-objective optimisation. The proposed framework cannot be applied using existing approaches for modelling maintenance. Existing modelling approaches using simulation have a number of limitations: The maintenance system is modelled separately from other inter-related systems such as production and spare parts logistics. In addition, these approaches are used to model one maintenance strategy only. A novel approach for modelling maintenance using Discrete Event Simulation is proposed. The proposed approach enables the modelling of interactions amongst various maintenance strategies and their effects on the assets in non-identical multi-unit systems. Using the proposed framework and modelling approach, simulation-based optimisation was conducted on an academic case and two industrial cases that are varied in terms of sector, size, number of manufacturing processes and level of maintenance documentation. Following the structured framework enabled discussing and selecting the suitable optimisation scope and applicable maintenance strategies as well as formulating a customised optimal problem for each case. The results of the study suggest that over-looking the optimisation of maintenance strategies may lead to sub-optimal solutions. In addition, this research provides insights for non-conflicting objectives in maintenance systems