Arena Simulation Models - Operations Management - Example

Introduction The company currently faces two option of producing the new product (Superwheel) while at the same ensures that there is production efficiency and maintains low production cost on the new product (Chary, 2004). In order to guarantee the above factors, the company should ensure that both option be run using the Arena simulation model in order to ascertain on the relevance of the model and concluding on the ideal production option that would be ideal, efficient and cost effective to the management. Option A The company intends to produce the new product with production processes that entails fewer production stages with less skilled forces. The consequence of the option is that, it will save time and money as well as minimize the production and operation cost. Care should be taken in suing this option since, adding a new production line to the existing processes; the company considers adding more machines or hiring more staff. Option B. This option entails the broad extend of using both the labor force as well as the use of machine in both loading. Processing and unloading the finished goods (Halevi, 2003). The net effect of the options is that, it would make the operation manager to consider other option or approach to adding the capacity to a new production line in order to enhance production capacity and at same time enhance production efficiency. Problem definition The company is currently facing the problem of identifying an ideal production and operation method that would best fit the company by way of cost efficiency as well as effectiveness of the new production line. The company therefore tries to ensure that the new production line would not affect the existing production line and tries to maximize on the profit to be generated from the new production line while remaining cost effective. Materials and equipment used in the research The company intends to use the following material and equipment in producing superwheel A. Human worker The company will use labor force in some processes such as the loading and cleaning point as well as at the unloading point (Christopher T. King, ‎United States. National Commission for Employment Policy, 1988). This will aid in minimizing machine error in handling the loading and offloading point and also minimize the operating cost. B. Machine X The company intends to use machine X in production of superwheel. This will help in reducing the operating cost as well as ensuring that there is production efficiency and time management. The sample were gathered on a random technique since, the approach was regarded as ideal approach in avoiding biasness as well as saving cost and time in ascertaining the relevance and importance of the option to be adopted by the management in processing super wheel. The sample was then prepared by the management accountant and production analyst in order to consider if adding new production line will be advantageous to the company in terms of cost reduction, efficiency in material usage and cost reduction. How measurement was made The measurement of the sample is then point on a five point scale and analysis made on the adequacy of the option to be adopted. In assurance a 99% confidence level on the sample collected, the analysis was then subjected to Arena simulation model and result generated were then analyzed for relevance, adequacy and efficiency prior to make informed conclusion which option to adopt based on material usage, time consumed in the production process as well as the confidence level that the result can be relied upon in making investment decision as far as operation management is concerned. The statistical techniques used upon the data. The data and information collected is then put on Arena simulation model for analysis. The final result generated is then analyzed based on the average mean, standard deviation and correlation between options (Greene, 1984). This statistical tool is Important since, it ascertain the risk and variance of each model as well as considering the ideal confidence level in which best model should adopted by the management in ensuring that ideal production liner is added to the existing processes as well as there is reduction in cost of the new product, improved efficiency as well as there is reported profit from the new product. Suitability of the simulation Model The simulation model adopted by the company is ideal in the production line to be introduced since, the model considers some statistical tool that is best for analyzing two correlated option as well as it provides a reliable output based on some degree of confidence level. Some of the factors that make the model suitable for operation management are; 1. Time The model considers time it takes for the project to be completed as well as the waiting time that a product must consume in the production process (Mark D. Hanna, 2006). The relevance of time is that, it gives an overview of the production delay, time in and out as well as the total time that a product will use in its production operation and thus it provides a better platform for ascertaining an ideal production option as far as time usage is concerned. 2. Resources The model ensures that a detail report on material usage is provided. This ideal since, material usage is important in ascertaining on whether to add a new production or not based on equipment available as well as new or existing labor force (Murthy, 2005). The company considers if the production option to be adopted will consume resource and if the option will lead to financial problem to the existing production processes. 3. Queue The model has the capability of identifying the time and volume of units in queues. The advantage is that it provides an ideal overview of ascertaining the best model with the least units in queues since, the main objectives of the model is to give the best model that ensure there is efficient production process that minimize processing time and volume of units in queue since, huge volume of units in queue would lead to high operating and maintenance cost and a reduction in profit to the company (Oh, 2010). Therefore, an ideal production process should ensure that there is small volume of units in queue with high output in order to guarantee on the new production line. Analysis of the simulation Result Option A Time The Total time on average is 374 with 1units of number worth 35.There is 1 unit of value of work in progress worth 17.78.this is an average system process since, the value of output is higher as compared to value of work in progress. The company should ensure that there is small value of work in progress with value of output in order to guarantee on the production efficiency. Queue The queue process for machine P depict an average value of 17.6279 with a maximum queue value of 34.this is quite high and it implies that machine P is having a high idle time which is not ideal for this process. Machine C do not predict any idle time since there is no any product on queue as depicted by the output results from the model. Resource; Usage The instantaneous utilization of material for machine P and C consecutively are 1, 0.8745 with a maximum value of 1.In this regard; it implies that machine P is operating under full capacity while machine C under utilization since it has not reached its maximum capacity. Both machines are busy and operating at full capacity (Richard B. Chase, 2006). Under scheduled utilization, machine P is fully operating while machine C is not fully occupied since, it can be depicted that machine C operate at 87% utilization capacity. Both machines should be operating under fully capacity in order to capitalize on least available resource while ensuring maximum profit is realized from new production line. Option B Entity The total number of input unit to the process is 148 with 74.8 units as work in progress. This implies that the units completed are 73.2.This quite a small unit since; the volume of output ought to be much higher as compared to volume of work in progress (Peter Jones, 2012). It is therefore an indication that there is high volume of queued item in process hence leading to more idle machine and man hours. The net effect is that it would lead to delay in production and high operating cost consequential from new production line. Resource; Usage The human worker is under full capacity while machine X is 99% usage. This is a good indication of machine utilization and its capacity and hence both machine and labor force is busy in the system. The resource therefore is properly utilized and consequently there is no delay or waste in resource utilization. Queue The queue process depicts an average of 73.78 units with a maximum of 148 units. This is unfavorable since, there is under utilization of resource and high idle time in the production process. In this regards, the number of units in queue ought to be minimized in order to guarantee on the efficiency of the production process and maximize on the limited resource to generate high profit from the new production line. Recommendations The company should consider Using option A in producing new product (Superwheel) since, the production process capitalize on the least available resource to generate high return in form of profit (Halevi, 2003). The option to be adopted portray a is small idle time depicted by the value of units in queue implying that there is ideal production efficiency with minimal operating and maintenance cost hence, the new production line would not affect the existing production processes since, the best option alternative to be adopted by the company in production superwheel will maximize on the resource and equipment to be used at low operating and maintenance cost. Option A should be adopted while considering the adequacy of the existing and required labor force in order to ensure effective production of superwheel. Labor force can be a limiting factor if proper care is not taken since, the new production process considers workforce at the loading point hence the company must as well as considers the new labor force. The equipment to be employed in producing the new product is machine X and thus the operating and maintenance cost ought to keep minimal in order to avoid unnecessary cost to the company that might lead to loss (Mark D. Hanna, 2006). The company must consider the efficiency and adequacy of the machine X in producing superwheel. This will lead to production efficiency since, guaranteed machine working hours would imply a reduction in operating and maintenance cost. In conclusion, the best option to be adopted by company would be effective where both labor and machine is available and efficient since, they are the key factors to consider in producing superwheel (PANNEERSELVAM, 2012). An ideal material usage is of paramount importance to the company due to the fact that poor resource utilization would imply an increase in unnecessary cost to the company hence generation of loss from the new product and to the existing production. In this regards, care ought to be taken in concluding on the result generated by the arena simulation model, since the model considers that the required available resource needed to produce the new product is readily available. Reference list Chary, 2004. Production And Operations Management - Page 2-6. Christopher T. King, ‎United States. National Commission for Employment Policy, 1988. Cross-cutting performance management issues in human. Greene, J.H., 1984. Operations Management: Productivity and Profit - Page 170. Halevi, G., 2003. Process and Operation Planning. Mark D. Hanna, ‎.R.N., 2006. Integrated Operations Management: A Supply Chain Perspecti. Murthy, P.R., 2005. Production And Operations Management - Page 1. Oh, S., 2010. Optimal Stopping Problems in Operations Management - Page 4. PANNEERSELVAM, R., 2012. PRODUCTION AND OPERATIONS MANAGEMENT - Page xv. Peter Jones, ‎.R., 2012. Operations Management - Page 79. Richard B. Chase, ‎.R.J.‎.J.A., 2006. Operations management for competitive advantage - Page 723. Vollmann, T.E., 1973. Operations management: a systems model-building approach. W. David Kelton, ‎.P.S.‎.B.S., 2010. Simulation with Arena. Read More