Availability and Stock Rupture Estimation By Using Continuous and Discrete Simulation Models (original) (raw)
Related papers
Simulation Modelling of Availability Contracts
Availability contract (also known as Performance-based Contract/Logistics) has been increasingly adopted in the context of Product-Service Systems (PSS). Despite the benefits, availability contract imposes major risks to the manufacturers due to the dynamic behaviour caused by the service delivery mechanisms. This paper aims to explore potential approaches that can be used to model the availability contract. The overall goal is to enable the manufacturers to assess the potential impacts of the contract to their manufacturing operations before actually committing to the changes. The work described in the paper involves the development of a simulation model from an example of an availability contract scenario. The outcomes from the simulation model provide an estimation of availability level, average delay and penalty cost subject to the given resource level and maintenance schedules. Based on this information, the OEM can decide whether the targets proposed in the contract is achievable. The outcome supports the potential and validity of the simulation approaches adopted in this study.
Evergreen, 2020
The time for cooling down and dismantling happens very fast so that spare parts have to be already available prior to the shutdown to avoid excessive downtime due to spare parts unavailability. This condition is common for most engines including machines in manufacturing plants, airplanes engines, ship engines, automobile engines, or heavy equipment in mining. However, this condition does not apply for gas turbines. For gas turbines, cooling down and dismantling are taking a few days and even more than 1 week. This distinctive characteristic has not been studied before. So, an integration model of spare parts inventory and preventive maintenance is proposed. The time factor of engine cooling down and dismantling will be taken into account by this proposed model. Spare parts will arrive after cooling down and dismantling period is finished using just-in-time method. The basic and proposed model are based on the case study from a power generation company in Indonesia. Discrete-event simulations (DES) are carried out using the company's historical data. The results of the DES simulation and data processing with formulas and commercial data are optimized by linear programming methods and response surface methodology (RSM). By incorporating the stochastic characteristic generated by the variations in the duration of cooling down & dismantling, the duration of assembling, and the duration of parts delivery, the application of the proposed model can reduce the duration of spare part inventory in the warehouse which will result to lower storage cost so that it can lead to an increase in the company's profit.
A Simulation Based Approach to Calculate Total Availability of a Complicated Production Line
2009
Calculating total availability time in a complicated production line by mathematical methods is a problem. In contrast to a simple production line where each station breakdown results in stop in production line, in complicated lines, breakdown effect of a station depends on other stations availability, intermediated buffer capacity and so on. In this paper, after expressing the importance of this problem, a simulation based solution is proposed. A simulation model of subject production line is developed and got run twice, the first run considers real availability pattern of production line and the second run supposes all stations are available. The ratio of outputs of these two runs shows the availability percentage of subject production line.
European Journal of Operational …, 2009
This paper compares two strategies for operating a production system composed of two machines working in parallel and a downstream inventory supplying an assembly line. The two machines, which are prone to random failures, undergo preventive and corrective maintenance operations. These operations with a random duration make the machines unavailable. Moreover, during regular subcontracting operations, one of these machines becomes unavailable to supply the downstream inventory. In the first strategy it is assumed that the periodicity of preventive maintenance operations and the production rate of each machine are independent. The second strategy suggests an interaction between the periods of unavailability and the production rates of the two machines in order to minimize production losses during these periods. A simulation model for each strategy is developed so as to be able to compare them and to simultaneously determine the timing of preventive maintenance on each machine considering the total average cost per time unit as the performance criterion. The second strategy is then considered, and a multi-criteria analysis is adopted to reach the best cost-availability compromise.
Optimization of maintenance and spare provisioning policy using simulation
Applied Mathematical Modelling, 2000
In practice, maintenance and spare parts inventory policies are treated separately or sequentially. To ensure availability of spare parts for a production system use, when necessary, there is always a tendency to overstock them. Excess inventory involves substantial working capital. The stock level of spare parts is dependent on the maintenance policy. Therefore, maintenance programs should be designed to reduce both maintenance and inventory related costs. In this paper, a manufacturing system is considered with stochastic item failure, replacement and order lead times of statistically identical items. The development of mathematical model for such a system is extremely difficult. A simulation model is therefore developed for the system operating with block replacement and continuous review inventory policy. The response of the system was studied for a number of case problems. The study clearly shows that the jointly optimized policy produces better results than that of the combination of separately or sequentially optimized policies.
2019
A maintenance strategy is an important factor in the production activities of the process industry. Since the process industry consists of many components, the failure mode is relatively complex. This paper observes one of the petrochemical companies in Indonesia which produces Pythalic Anhydride. The company is able to produce in 20.69 days every month. In reality, during 2017, the company produced 23 days every month on average. Production, known as the calendar day, which cannot achieve the target can affect customer service level. This research focuses on evaluating availability in order to minimize Mean Time to Repair (MTTR). One of the best strategies is to control the spare part inventory policy so that the spare part must be available when an equipment downtime occurs. We will use two modeling techniques to solve the problem: (a) reliability block diagram will be used to model the failure mode and (b) the simulation model will be used to model the entire system, including random variables and variable inter-dependency. After conducting scenario analysis by varying some parameters, the availability increased to 91.8% and average calendar days decreased to 22.64 days per month.
Annual Reliability and Maintainability Symposium. 2002 Proceedings (Cat. No.02CH37318), 2002
With the increasing air traffic and growth of deployed FAA equipment, high equipment availability and low outage time is also becoming more important. While the use of simulation models and simple queuing models for assessing the impact of staffing on availability has been available for more than 5 decades, it has not been widely used because of the cost and complexity of implementation. This paper presents an analytical model and software tool that can be used by non-experts to relate FAA maintenance resources including staffing, training, shift allocation, and geographical deployment to National Airspace System (NAS) facility and service downtime and availability. The analytical methodology and tool presented in this paper make it possible for any user to rapidly assess how changes in staffing, training. equipment count, and reliability will impact outage time, availability, maintenance backlog and technician utilization. It allows users to easily perform parametric studies on a variety of "what if' scenarios related to economics and capacity. The most significant benefit is that these results can now be made available to analysts and decision makers. The net result will be more informed decisions to account for the i m p a c t of maintenance resources on NAS capacity and overall economics.
International Journal of Mathematics in Operational Research, 2015
Many engineering systems are subjected to deterioration, meaning that during the course of time their conditions fall to failure levels. Such systems and their components are either repaired at failure or replaced before or after failure. However not every deterioration can bring about sudden failure of the system. Some deterioration can slightly reduce the strength of the system until at some point failure occurs. Such deterioration is said to be minor deterioration. This paper deals with the modelling and evaluation of availability of a system subjected to minor deterioration under imperfect repair. In this paper, we developed the explicit expression of system availability using probabilistic approach and determine the effect of failure, repair rate and number of states on system availability. The optimal availability level the system can attain is also determined. The results of this paper will enhance the system performance and useful for timely execution of proper maintenance improvement, decision, planning and optimisation.
Availability model of technical objects—block inspection policy implementation
Safety and Reliability: Methodology and Applications, 2014
In the presented paper, authors focus on development of mathematical delay-time model for single-unit technical systems liable to costly failure. Failure is taken here to mean a breakdown or catastrophic event, after which the system is unusable until repaired or replaced. Thus, the briefly literature review in the area of delay-time modelling is provided. Later the analytical model of expected system availability is investigated. Authors also discuss the sensitivity analysis of given simulation model. The directions for further research work are defined.
International Journal of Industrial and Systems Engineering, 2015
Production control in a failure-prone manufacturing system (FPMS) is studied in the present paper. FPMS are those which are subjected to random breakdown assumption and corrective and preventive maintenance are considered for them too. In order to prevent shortage, buffer is used in these systems. Determining the inventory level of the buffer is one of the most important parameter. Another effective parameter is determining the time of period for preventive maintenance which is important to discover breakdowns before their occurrence and thus minimise the cost of corrective maintenance. The purpose of this paper is to determine the optimal production rate and time of period for preventive maintenance for an FPMS to minimise sum of holding shortage, corrective and preventive maintenance cost. To this end, discrete event simulation is used. Studying the system under conditions where analytical solution is not possible is the most important advantage of simulation method.