Application of Discrete Event Simulation Model - Case Study Example

Application of Discrete Event Simulation Model By Professor Class University City Date of submission Application of Discrete Event Simulation Model Introduction Currently, firms operate in complex systems that are continually changing and improving with time. Therefore, it is important to understand the systems and the prevailing factors affecting the efficiency of the operations. To simplify and recognize the problems affecting the systems or models, which imitate the actual systems, are developed. Simulation therefore, is a process that imitate the real world scenario to forecast and enhance the efficiency and performance of the models. It is possible to use these simulation models in different industrial situations as within engineering firms, assembly lines, healthcare, commercial institutions, retail shops or even used for virtual games. The simulation technique that is extensively gaining popularity is the Discrete Event Simulation (DES) for example the customer-arriving and customer-leaving model whose primary objective is to reduce the waiting time for the customers (Molter, 2012, 125). Moreover, simulation involves the generation of systems’ history and observations artificially to draw the inferences that relates to the characteristics of the operations that represents the actual system. The major advantages of using the simulations as modelling tools relate to flexibility, ability to shorten and increase time parameters, and explore various procedures for identification of the strengths and problems. CASE STUDIES The Dow Chemical Engineering Plant (Bottleneck analysis using DES) Dow is an American manufacturing group of companies that deals in chemicals that began in the 1980s as a bleach company. The case study represents the presentation at the Winter Simulation Conference held in 2010 Baltimore USA. Reasons behind use of DES and problems requiring solutions Bottleneck within any manufacturing company could be considered as a constraint on the capacity of slowing down the production processes or to some extent halt the production processes. From such context, it is inevitable to check regularly the bottleneck within the production line whose primary role involve improving the rate of production rate within the firm. Besides, from the nature of the chemical plant, these companies have complex manufacturing unit whose complexity tend to increase due to the discrete and continuous flow of the product during the processes involved in manufacturing. Since DES deals with the input data randomly within different time spans, it plays a crucial role as a simulation technique. Other organizations that successfully utilized the application for detecting the bottlenecks like discrete event models are Toyota Motor Company. Dow found the DES model fruitful. Therefore, the applicability of the DES model for the bottleneck analysis is evident within the firm. The conducted analysis is part of the Sigma process that plays a significant role in determining the cause of the problem reducing the production rates. In addition, chemical operating firms have several system interactions, which vary to make it further difficult to carry bottleneck analysis. Considering these factors, the company decided to use DES that captures these complexities with comparative ease. Difficulties overcome when installing DES When implementing the DES model, the experts within the Dow firm experienced numerous challenges that they had to address. Therefore, they had to identify the best DES software that would help enhance efficiency as well as finding the distribution for the processes and flow rates through the whole simulation process. To improve efficiency and accuracy of the predicted bottlenecks, the company came up with the strategy that would hell analyse the results, which led to the deep study required for finding the simulation settings to yield the maximum results required. It is from such background that the company modellers came up with the idea to utilize ExtendSim as their DES software since it offers hierarchical modelling expertise (Strickland, 2012, 243). The modellers retrieved the required data from the organizational servers and used the JMP statistical software to generate various distributions and flow rates required as inputs for the DES model. From the analysis, the modellers create three different databases of which the first was from input to software, second for the dynamic variables input for the DES model, and the third for storing the results meant for the analysis of the production rates. The extent of improving the efficiency depends on the comparison made between the findings of the model and historical data of the company like production rates wait time for the products, and process times. Benefits of using the model Upon successful validation of the model, the company was able to identify the bottleneck of each product. The table below shows a summary of the findings derived from the 1st and 2nd level bottlenecks in each product and their generating to be addressed in sequence to achieve an improvement in production. In product B, there was a limitation due to reduced production rates within the 1st level of the bottleneck, Processes 3 and 4. With the elimination of issues in Process 3 and 4, only Process 2 of the 2nd level would be limiting the production of the plant. To find the 2nd level bottleneck, there was a need to eliminate the throughput of the 1st level bottleneck artificially to expose the next limiting stage. Table 1. Sample report indicating bottleneck levels for various products Product Process 1 Process 2 Process 3 and Process 5 Process 6 Name Process 4 A 1 2 B 2 1 C 2 1 Table 2. Sample report showing production improvements with 1st level bottleneck removal Product Production rate us- Production rate using simulation by removing 1st level bottleneck (batches/day) Percentage improvement Name ing simulation in an average production rate (batches/day) A 10±0.11 11±0.1 10% B 8±0.1 9±0.1 13% C 7±0.1 8±0.1 14% Simulation flow The figure above represents the high-level overview of the operations taking place within the plant with notion on whether the process in question is batch or continuous. Even though the presentation is sequential, several parallel and converging paths are present for the material flow. The initial stage represents preparation of the required type of the raw material for process 2. There is processing of the batch raw materials using the equipment in process 1 operating in parallel N2, which is the number of the storage tanks. At each point in time, a batch of raw material is transferable to a single storage tank (Storage 1) with the ability to hold one batch. Within the system, there are N3 numbers for carrying out Process 2. Upon the availability of the equipment, a batch of raw materials from the storage tank 1 is transferred. With the completion of the process, there is transfer of the batch to the next storage tank and the process continues. There is staging of different equipment used in carrying out process 2 to streamline production that implies that parallel equipment does not begin and complete their operations similar time. Such interactions ensure that the equipment transfer only completed batch at equal intervals of time without simultaneously waiting for other storages to be empty. Description of the DES software used by the company ExtendSim is one of the most powerful simulation tool used in developing dynamic models of already existing or proposed processes in different fields. It is possible to use the software in creating models from building the blocks, exploring the involved processes, and analysing the manner in which they relate. The modellers only require the software and imagination to create professional models that meet the business needs. ExtendSim is easy to use and helps to understand the complex systems for producing better and faster results. With the software, the company can predict the course and results of some actions, gain insight and arouse creative thinking, and assist in visualizing the processes logically. Besides, it helps to identify problems before implementation, offers an opportunity for identifying and exploring the potential effect of modification. It also helps to evaluate inefficiencies and understand the occurrence of events (Bikram & Bury, 2010). This simulation program models discrete event, continuous, agent-based, and discrete rate processes. There are four ExtendSim packages including continuous processes (CP), operation research (OR) that adds the discrete event, advanced technology (AT) adding the discrete rate, and several advanced modelling characteristics, and Stat:Fit meant for statistical distribution fitting while the Suite for adding the 3D animation. The software creates models through dragging the blocks from the model worksheet. There is a connection of the blocks to create the logical flow. Besides, the blocks and proprietary also accommodate the data parameters. However, it is possible to create new blocks through combination of the existing blocks to form a single hierarchical block. Application of DES in Pepsi Company for User Support helpline The company produces carbonated soft drink. As a global company, Pepsin Co. receives many queries related to production processes and inquiries from the potential clients. These activities require an effective and reliable means of communication, which led to application of simulation model. Why the company uses DES and problems experienced The major problem that triggered the concern to use the simulation model was the magnitude of information received by the organization. In addition, most people were making numerous enquiries considering it is global institution. Pepsi Co. uses the Information System Support Unit (ISSU) as its DES simulation program to address these problems and provide support for the IT requirements of the organization. The major problem within the institution was the support line, which provides assistance in software installation and consumption. Because of these problems, the company had bad reputation for not taking the queries and answering them on time when require by the potential clients. To add more pressure on the company, it was focusing on introducing IT department within all its facilities existing in different countries. These activities would, in the end, increase the workload on the supporting staff. Therefore, the company considered DES to be the solution of such problems to assist finding the desired number of support staff and the appropriate methodology. Since the company had several employees trained on matters related to simulation modelling, it decided to settle on DES model. The model was required to have the arrival of request, logging of request, picking request, and solution to the issues on request. In addition, the program required the part-time workers and permanents employees to follow the scheduled support activities. However, the information on how much time request could take was unavailable which means they had to prepare a possible time for the same (Swain, n.d). To complete the scenario, the company used Witness as a DES package mode in completing the scenario. Benefits experienced after using DES The model provided help to both the staffs and potential clients. On a daily basis, workers forget their organizational user ID or passwords for their logging site. With the programme, they are able to make online request for their credentials and receive them securely through the email within a second. Upon logging into the model, on demand assistance is just a click away with the information of the screen for sensitive matters. Every simulation comes with demos that self-spaced which accounts the speeds of understanding of the employees, comprehensive manuals, and database with FAQ that is available online and important glossary of business related terms (Torrenzano & Davis, 2011, 194). Moreover, if they do not receive their desired answers through the on-demand support system, then those forwarding inquiries are at liberty to seek clarification from the interpretive section that has highly qualified customer assistance team. To the clients, the system offers customers support on the technical questions submitted through the simulation within 24 hours. To work effectively, the DES model require the clients to submit their queries in written formats online to ensure that the questions answered only relate to simulation technicality. The institutional policy ensures that there is no unfair advantage to other clients who call. If clients forward issues that are difficult to handle through emailing, then the management contact them to address the issue. The actual benefit of the model to the clients is the meaningful conversation occurring as the main concept that it brings to life. Besides, the customer support team have proficiency in answering appropriate technical questions relating to simulation to prevent interference with the interactions. Problems experienced during installation of the programme The major problem with installation of the programme was compatibility issue to outdate systems. Moreover, the organization was unable to deploy the software hence receiving an error message identified as ‘fatal error due to installation process.’ The possible cause of the problem include prior existence of the software within the system, the used user name in the ‘Run As’ option for defining the configuration lacks the privilege of installing the programme, and generic issues associated with the machine-specific issues. Besides, the outdated machines had insufficient space for installation, unclean temporary directory, and locked files within the systems. Software installation also required internet connection to establish the link with the server. Nonetheless, with rising problems associated with connectivity, the company experienced installation problems that led to increased installation cost. The company had also to replace all the outdated programmes and equipment to accommodate the requirements of the new system. Description of the DES software used by the company Considered as one of the leading simulation models with more than 6000 systems existing globally, Witness software plays an important role in enhancing reliability and efficiency. The programme has been used successfully across wide range of business applications in both manufacturing and service industries. Through the years, it has undergone facelifts and currently incorporates many functionalities. Generally, the programme is suited to environmental modelling since its ease use allows for flexibility and rapid deployment of the applications. With the programme, it is possible to set characteristics parameters for different machines and processing times to allow the ‘what if’ analysis of distinctively occurring scenarios. In most cases, the developed models allow the machines and other systems within plant including the possibility of taking the semi-finished products from external sources. Conclusion The market is becoming highly competitive that requires excellence in quality for the innovative changes that would help improve the processes. However, the changes should be substantial enough to improve efficiency and cost effectiveness of the organizational processes. These changes have several risks. The DES model is quite beneficial in identifying these risks and analysing them. From the case studies, it is clear that the model improves efficiency and reliability in both engineering and commercial organizations. Moreover, in commercial firms it improves the quality of services offered as it ensures the clients receive their feedback on time. Through utilization of the random occurrences of events in the business process history, it is possible to use DES in imitating the changing business behaviour. Such analysis are important in the decision-making process within the industry. Most businesses are currently implementing different DES business models. The future of DES in business industry revolves around Probabilistic and Deterministic that uses probability distribution in representing stochastic process while deterministic uses events input into the simulation to produce similar set of simulation. References Bikram, B., & Bury, S. J. (2010). Bottleneck Analysis of a Chemical Plant Using Discrete Event. Retrieved from http://www.informs-sim.org/wsc10papers/142.pdf Molter, H. G. (2012). SynDEVS co-design flow: A hardware/software co-design flow based on the discrete event system specification model of computation. Wiesbaden: Springer Vieweg. Strickland, J. (2012). Discrete event simulation using ExtendSim 8. United States: Lulu.com Swain, J. J. (n.d.). Software Survey: Simulation — Back to the future - INFORMS. Retrieved from https://informs.org/ORMS-Today/Public-Articles/October-Volume-38-Number- 5/Software-Survey-Simulation-Back-to-the-future Torrenzano, R., & Davis, M. W. (2011). Digital Assassination: Protecting your reputation, brand, or business against online attacks. New York: St. Martin's Press. . Read More

Besides, from the nature of the chemical plant, these companies have complex manufacturing unit whose complexity tend to increase due to the discrete and continuous flow of the product during the processes involved in manufacturing. Since DES deals with the input data randomly within different time spans, it plays a crucial role as a simulation technique. Other organizations that successfully utilized the application for detecting the bottlenecks like discrete event models are Toyota Motor Company.

Dow found the DES model fruitful. Therefore, the applicability of the DES model for the bottleneck analysis is evident within the firm. The conducted analysis is part of the Sigma process that plays a significant role in determining the cause of the problem reducing the production rates. In addition, chemical operating firms have several system interactions, which vary to make it further difficult to carry bottleneck analysis. Considering these factors, the company decided to use DES that captures these complexities with comparative ease.

Difficulties overcome when installing DES When implementing the DES model, the experts within the Dow firm experienced numerous challenges that they had to address. Therefore, they had to identify the best DES software that would help enhance efficiency as well as finding the distribution for the processes and flow rates through the whole simulation process. To improve efficiency and accuracy of the predicted bottlenecks, the company came up with the strategy that would hell analyse the results, which led to the deep study required for finding the simulation settings to yield the maximum results required.

It is from such background that the company modellers came up with the idea to utilize ExtendSim as their DES software since it offers hierarchical modelling expertise (Strickland, 2012, 243). The modellers retrieved the required data from the organizational servers and used the JMP statistical software to generate various distributions and flow rates required as inputs for the DES model. From the analysis, the modellers create three different databases of which the first was from input to software, second for the dynamic variables input for the DES model, and the third for storing the results meant for the analysis of the production rates.

The extent of improving the efficiency depends on the comparison made between the findings of the model and historical data of the company like production rates wait time for the products, and process times. Benefits of using the model Upon successful validation of the model, the company was able to identify the bottleneck of each product. The table below shows a summary of the findings derived from the 1st and 2nd level bottlenecks in each product and their generating to be addressed in sequence to achieve an improvement in production.

In product B, there was a limitation due to reduced production rates within the 1st level of the bottleneck, Processes 3 and 4. With the elimination of issues in Process 3 and 4, only Process 2 of the 2nd level would be limiting the production of the plant. To find the 2nd level bottleneck, there was a need to eliminate the throughput of the 1st level bottleneck artificially to expose the next limiting stage. Table 1. Sample report indicating bottleneck levels for various products Product Process 1 Process 2 Process 3 and Process 5 Process 6 Name Process 4 A 1 2 B 2 1 C 2 1 Table 2.

Sample report showing production improvements with 1st level bottleneck removal Product Production rate us- Production rate using simulation by removing 1st level bottleneck (batches/day) Percentage improvement Name ing simulation in an average production rate (batches/day) A 10±0.11 11±0.1 10% B 8±0.1 9±0.1 13% C 7±0.1 8±0.1 14% Simulation flow The figure above represents the high-level overview of the operations taking place within the plant with notion on whether the process in question is batch or continuous.

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