Simulation and Systems Modelling - Example

Name : xxxxxxxxxxx Institution : xxxxxxxxxxx Course : xxxxxxxxxxx Title : Simulation and Systems Modelling Tutor : xxxxxxxxxxx @2011 SIMULATION AND SYSTEMS MODELLING Introduction Simulation entails the design of a given real system and its use in the conducting of experiments so as to better understand the behavior of the system in question. It may also be used in the evaluation of various strategies made use of in the operation of the system in question. Simulation can be categorized into discrete event, hybrid or continuous based types on the basis of the way in which the model represents the changes of state within a given modeled system. Simulation is a cost effective tool of analysis that is made use of by engineers to assist them and their managers in quick and reliable decision making. Applications of Discrete Event Simulation in the Design of Automotive Powertrain Manufacturing Systems (Production Modeling Corporation) The manufacture of automotives is a complicated task that needs the integration and production of thousands of various components. The powertrain system is among the vital parts of each and every automobile. The transmission and the engine are the vital components that make up the powertrain system. The manufacture of engines and good quality transmissions constitute an automobile’s good quality. Typically all the necessary sub-assemblies or automotive components for instance transmissions and engines are separately produced and assembled to one another and finally to the chassis at the final assembly stage of a given automobile. It therefore follows that the different parts of an engine for instance crankshaft, camshaft etc are sub-assembled in different areas and then put together at a final stage to constitute the engine. Discrete event simulation is thus a standard tool that is made use of in designing and implementing various automotive manufacturing systems that range from a given connecting rod sub machining system to an automotive assembly system. Among the successful applications of discrete event simulation are obtained from Ulgen et al. 1994, Jeyebalan et al. 1992 and Gunal et al. 1996. Most automotive companies for instance the big three car manufacturing companies based in the United States (General Motors Corporation, Chrysler Corporation and Ford Motor Company) currently need a modified and new manufacturing system design (Ulgen et al 1996). Simulation applications that exist in the automotive industry maybe classified into four major applications areas for example; use in the assembly of vehicle parts, use in the assembly of different vehicle components for example transmission plants, stamping and engines. Application in the assembly of small component plants for example small metal parts, starter plants, electronics and small metal parts. Lastly, they have also been applied in logistics and Supply chain. According to Jayaraman and Gunal 1997, the most common objectives for the utilization of discrete event simulation systems are; bottleneck detection, the optimization of shift patterns, the design of material handling systems, the comparison of operating philosophies, determination of system throughput, analysis of the storage issues of various materials and manpower optimization and allocation. Below is a figure that shows a typical engine set up; Load Engine Blocks FLOW Unload completed engines TESTING AREA FLOW Summary of the Case Study The case study in question is an illustration of the benefits of the utilization of discrete event simulation in the repair area and the final engine test of powertrain assemblies. In each and every transmission and engine assembly, one of the very last steps in its assembly is testing. Testing is conducted on each assembly at a specifically designed test stand. It is typical for test stands to take up a lot of processing time as compared to other stations available in the system. It is also noted that repair operations depict random process time in conjunction with the type of faults that occur in a given engine assembly since they may manifest due to a number of different reasons. The aforementioned characteristics imply the utilization of a number of test stands. In typical set-ups each and every test stands are connected to entire assembly lines via conveyors, it therefore follows that test station arrangements are essential for ensuring that the costs are minimal and that demand is satisfied. With the provision of testing area dynamics, simulation is most often applied in the evaluation of various alternatives and the selection of the best configuration. In section 2 of the case study, a distinctive engine assembly manufacturing arrangement is introduced with particular attention given to the problems that can be taken care of by simulation. In section 3 of the case study, a detailed discussion of the need for simulation in the analysis of system is taken into consideration. The illustration of the utilization of simulation in design of comparable areas is stipulated in section 4. The conclusion of the case study is given in section 5 (Jayaraman & Gunal, 1997). Reasons for the use of DES Jayaraman & Gunal suggest that among the advantages of DES are that they are able to in-corporate the impacts that come with randomness of a given system. The software systems also provide for the ability to model indiscriminate downtime occurrences that are accompanied by variable repair and cycle times. Its use also allows for the evaluation of different alternatives that are subject to the diverse values of parameters that are made use of. For instance a sensitivity analysis on each and every option can be conducted through the modification of the vital parameters. A good example is when process engineers and designers are able to determine the maximum permissible time to repair a malfunctioning engine. The aforementioned move will aid with various decisions for example whether the manpower that is being utilized in repair area is tantamount to being increased for the achievement of smooth flow. Problems before the use of DES Production Modeling Corporation experienced a number of faults during engine assembly. They needed a system that would allow them to analyze a number of different alternatives and hence aid in the selection of the best system configuration. Benefits after the use of DES The use of simulation allows for the analysis of the following design parameters; the time of repair for rejected pallets, in-line versus off-line operation mode, transport and conveyor speeds, the arrangement of various parallel stations so as to ensure the optimal utilization of space, the number of cycle times for respective parallel stations and the mode of sequencing pallets into the uniform utilization of stands. Obstacles and their Overcoming There was some difficulty in the division of tasks among a number of stations. For instance the testing operation as it ideally requires a given amount of time; twice or thrice of a given cycle time which can be obtained in other stations. Since the maximum cycle time in any given station that exists along a given assembly line is not permissible to be more than a given line rate. Then, the maintenance of a given line rate of various testing stands are mirrored such that the engines are processed in parallel fashion. Simulation is thus advantageous since it allows for the inclusion of the impact of randomness in various systems. DES is able to accommodate the aforementioned manufacturing system parameters. DES is useful in the evaluation of different alternatives subject to its various parameter values. It allows for this since it allows for detailed animation capabilities. The animation of various assembly line operations aid engineers to visually detect bottlenecks or problems and as such test out alternate design lines. A good example of the utilization of DES is in the determination of the maximum allowable time in the repair of a given faulty engine (Jayaraman & Gunal, 1997). The obtained results will aid in other decisions for instance the number of manpower required in the area of repair so as to affect a smooth flow. DES allows for the effective analysis of the installation of quality checks at a reduced cost. Simulation provides an easy means in the evaluation of different strategies needed before the generation of PLC code. The best strategy in the distribution of pallets to manual workbenches maybe optimized by the use of simulation rather than their testing during implementation. DES software system AutoMod™made use of in automotive industries is a DES tool channeled towards material flow in the design, analyses and the operating manufacturing systems. It is made use of in the solution of queueing, material handling and manufacturing problems. Its 3-D real-time feature and its interaction facility sustain the user designing, debugging and the editing of complex manufacturing problems (Rockwell Software, 2011). AutoMod Software from Brooks Automation permits an institution to experiment with the use of ‘What if’ scenarios and as such experiment with alternative design ideas for use in manufacturing, warehousing/ distribution facilities and material handling. The software supports the use of English as a language. It supports the following operating system technologies; Windows 95/98/ME, Windows XP/2000/NT. The prices are based on modules and go for $18,000 (Brooks Automation, 2011). The hardware platforms required for it to run is PC 9×/NT/2000/XP platforms and they need a minimum of 8MB RAM to be able to run. Applications of Discrete Event Simulation in the Design of Healthcare Systems (National Health Service) Introduction DES is being made use of in numerous healthcare areas for instance in Emergency Departments (ED) for the modeling of operations and also for the analysis of patient throughput time and flows. DES has found application in the forecasting of future capacity expansion and requirements of existing or new ED facilities. DES has also been integrated by other techniques for example Six Sigma and Integer Linear Programming (ILP) for use in given applications. Summary of case study The case study at hand transcends the application of DES in managing and theatre operations. The application of DES is described in the modeling of the various complex relationships that exist in case mixes, between patient types and operating theatre allocations that exist in large National Health Service (NHS) Trusts located in London. In the case study at hand, the simulation model that was come up with outlined the main features that existed in nine theatres that lay focus on patient throughput times and operational processes. The model was utilized in the testing of three case scenario mixes and also to demonstrate the potential of the utilization of simulation modeling as a means of testing the health care operations. Simulation modeling was seen as a cost effective technique for comprehending the issues that pertain to healthcare operations management in conjunction with simulation technique’s roles in problem solving. The results of the case study showed that the removal of all day cases resulted in the reduction of patient throughput by around 23.3% and the employment of orthopedic theatre was recorded at 6.5%. The case is thus a manifestation of the manner in which healthcare managers could gather the necessary information required in decision making. The methodology made use of in the case study was derived after the analysis of the hospital’s current activities. The hospital’s current activities entailed the thorough description of the various theatre operations, the frequency of theatre use and the manner in which it is made use of that is the patient’s pathways which were the basis of model’s logic. As per the case study; utilization is an indication of the manner in which the available resources are made use of. Throughput in the study refers to the quantity of work that has been passed through the system in a given period of time. The figure below shows theatre 1 Scheduled by Utilization Scenario Utilization 3.0 2.0 1.0 0.0 Scenario 0 Scenario 1 Scenario 2 Scenario 3 Reasons for the use of DES The company decided to make use of DES in the bid to obtain information that would aid management in the making of decisions with regard to their real system. The DES approach was seen as a cost effective approach. The service managers in the hospital were interested in the obtaining of the best scenario of a given case mix without affecting the utilization and throughput levels which are viewed as the backbone of a properly run system. Problems before the use of DES The hospital managers were not able to make measurable comparisons between situations and as a result were not able to make informed decisions and predictions. It has been noted that spreadsheet data analysis methods are not as advanced in the capturing of the dynamics of a given system as effectively as DES. Benefits after the use of DES The hospital managers were able to obtain quantifiable measurements needed for their analysis. The DES model made use of in the case study clearly outlines in quantifiable terms the extent of the impact of each and every scenario (case mix). Figure 3 in the attached case study. (See appendix below). The model clearly stipulates, in quantifiable terms the extent to which each scenario impacts the chosen performance measures (patient throughput and theatre utilization). In light of the aforementioned, scenario 1 (without cases) may be the option preferred since it affects performance measures to the least. DES is very efficient on the problem solving and in understanding since it may be able to quantify the effect of a given scenario while taking into accounts various system dynamics and behavior. The aforementioned implies that DES is thus a reliable and useful tool in the enabling of clinicians and service managers in confidence decision making. Obstacles and their Overcoming The development of an accurate picture of current activities (the basis of operation of DES) was not very easy. For example patient preparation; the administration of anesthetics varies and as such a specific time of entry is tantamount to fluctuations. It was corrected by the use of histograms and as such the obtainance of normal distribution. There were instances in which the data required in the generation of the model was not available. In these instances the opinions of managers/clinicians were relied upon for instance the classification of operations into ‘major’, ‘intermediate’ and ‘minor’. DES software system Simulation was achieved through the utilization of Arena Simulation Software obtained from Rockwell Automation. The DES model that was made use of had the following vital elements; patients, theatres (resources) and the process paths. The model comprised of a number of activities between when a given patient left the ward to the theatres and when the patient returned to the ward soon after recovery. The hardware platform required by Arena Simulation is WITNESS and its price fluctuates based on its versions; Arena Basic 13.5 goes for $ 1,895, Basic Edition Plus 13.5 goes for $7,500, Arena Standard Edition 13.5 goes for $15,500 and Arena Professional 13.5 goes for $ 19,500. DES Technique and the Business or Finance Sector According to Rockwell Software (2011), DES can be made use of in the business sector. This is due to AutoMod’s feature in permitting itself to model a virtual system from service industries to manufacturing industries. It allows for a user to be able to evaluate alternatives, determine control strategies, conduct training, test concepts and respond to questions that pertain to system capabilities. Its aforementioned functionalities therefore enable it to be used in business and finance sectors for instance in the prediction of stock behavior in various stock exchanges around the world. Training is a universal aspect of any given business and as such the use of DES can therefore be facilitated and as such its use in industries other than manufacturing industries. The three big manufacturing companies in the United States (Ford Motors, General Motors and Chrysler In-corporation) make use of AutoMod (Ulgen et al 1996). Also the use of Arena Simulation software has allowed businesses to develop their businesses through the playing out of ‘what if’ scenarios and as such develop themselves as used by National Health Service (Gore et al, 2003). Opinion on use of DES DES has numerous applications in various industries and more research will enable it to be used widely in more advanced ways. According to Johannsson 2002, DES is yet to be modified to be able to create order in-conjunction with the structuring of data, knowledge and information of the various manufacturing process systems. Conclusion The DES system that was made use of in the hospital setting was utilized in the prediction and the understanding of the weight of impact of various case mix situations that affect patient throughput and the use of theatres. DES was utilized as a form of evidence based approach. In Production Modeling Corporation DES was made use of in the analysis of engine assembly and as such the monitoring of throughput and the minimization of cost. The study on simulation has given me an insight of the manner in which complexities in a number of sectors can be simplified at a cost effective way. It has also enabled me to realize that predictions can also be easily made by its use; the ‘what if’ scenarios allowed for by Arena Software. References Jayaraman, A & Gunal, K (1997). Applications of Discrete Event Simulation in the Design of Automotive Powertrain Manufacturing Sytems. Gore, J, Mousavi, A & Komashie, A (2003). Using Discrete Event Simulation (DES) to Manage Theatre Operations in Healthcare: An Audit-based Case Study Ulgen, O & Gunal, A (1996). Applications of Simulation in Automobile Industry. Retrieved 21st May, 2011 from http://www.pmcorp.com/PublishedPapers/Simulation%20Publications/Sim- Methodology/AutomobileIndustry-Chapter15.pdf Rockwell Software (2011). AutoMod. Retrieved 21st May 21, 2011 from http://www.satgmbh.de/320_e.htm Design Rate Simulations (2010). Simulation Software List. Retrieved 21st May, 2011 from http://www.design-rate.com/simulation_software.htm Brooks Automation (2011). Planning and Logistics Solutions. Retrieved 21st May from http://www.softscout.com/software/Logistics-and-Inventory/Logistical- Simulators/AutoMod.html Bjorn, J (2002). Thesis for the degree of licentiate of engineering / Department of Product and Production Development, Chalmers University of Technology, ISSN 1651-0984; nr 7. Retrieved May 23, 2011 from http://publications.lib.chalmers.se/cpl/record/index.xsql?pubid=7560 Appendix Appendix: Case Study (Auto Mobile) Available at: http://www.google.co.uk/#hl=en&xhr=t&q=APPLICATIONS+OF+DISCRETE+EVENT+SIMULATION+IN+THE+DESIGN+OF+AUTOMOTIVE&cp=69&pf=p&sclient=psy&site=&source=hp&rlz=1R2ADRA_enGB426&aq=f&aqi=&aql=&oq=APPLICATIONS+OF+DISCRETE+EVENT+SIMULATION+IN+THE+DESIGN+OF+AUTOMOTIVE&pbx=1&fp=a9b9aa294c8c9b68 Case Study: Final Test Area Design The following is a description of a test area that was subject to an analysis using simulation. The objectives of the study were to determine whether there would be a need for buffers, and to determine the best model of operation regarding the control of traffic in the testing area. First, the system is described with the discussion of potential issues that required the use of simulation. Then, a summary of the study is given with significant results. 4.1 System Description There are two major types of testing in a typical engine assembly system: the leak test and the cold test. During the design of an assembly line, once the problem of the test stand cycle time and the number of initial number of stands is determined, the relative location and arrangement of stands should be considered. Certain constraints affect this decision. The most important constraint is layout related. Automotive plants are typically constrained for plant space. Efficient arrangement of test stands (typically space consuming) is important to saving space. Another constraint is the fact that test stands have some special requirements for additional equipment such piping for water and gas. Consequently bringing the test stands closer together is very desirable. Since time on test stands is scarce, it is essential that all stands are highly utilized. However, if other stations upstream from the stands (especially the automatic stations) are down for extended periods of time, the test stands might be starved for pallets. To avoid this situation, some form of buffer in front of the test stands serves well increasing the area requirements. Further, to keep travel distance to a minimum, it is desirable to keep the repair area close to the test stands. Appendix II Using Discrete Event Simulation (DES) to Manage Theatre Operations in Healthcare- An Audit Based Case Study. Available at http://dspace.brunel.ac.uk/bitstream/2438/2606/1/Using%20Discrete%20Event%20Simulation%20%28DES%29%20to%20Manage%20Theatre%20Operations%20in%20Healthcare-%20An%20Audit-Based%20Case%20Study.pdf Methodology The structure of the simulation model that was developed is based on patient flow through nine theatres. It was necessary to commence with an accurate description of the operations of the theatres to provide a current picture of activity that would be used in the model. This was achieved by conducting a service audits, involving routine activity data analysis and discussions with managers. Throughout was assessed, various activities and waiting areas defined, and different routes (pathways) that patients may take during a visit identified. DES was then applied, as described in the proceeding sections. Operation of the theatres Most of the nine theatres at the Trust site were dedicated: Theatre 1- Ear, Nose and Throat (ENT) Theatre 2 – Urology Theatre 3- General Surgery Theatre 4 – Elective Orthopaedic Theatre 5 – Colorectal Theatre 6 – Gynaecology Theatre 7- Monday: Other Unit; Tuesday; Community Dental etc. Theatre 8 – Vascular Theatre 9 – Orthopaedic Trauma The theatres are served by one transfer control area and one recovery unit. Each theatre however has a dedicated anaesthetics room. Theatre Schedules The theatres are scheduled to operate in one of the following modes; Morning list (8.30-12.30) Afternoon list (1.30pm – 5.30 pm) All day list (8.30 to 5pm) Private Ops (Theatre 7 on Wednesdays.) Reserved for another unit (Theatre 7 on Mondays) Comm. Dental ops (Theatre 7 on Tuesdays) Idle The current model only considers NHS patients; hence theatre 7 is modeled as not being available on Mondays, Tuesdays and Wednesdays. Regular operations of the theatres take place from Monday to Friday 8:30 to 17:30 even though emergency cases are outside these hours. The simulation model was constructed to reproduce the various paths that patients can take in the theatres. This was done in consultation with staff of the department who have expert knowledge of its operations and through analysis of theatre activity data. The three important elements of this model are the patients, theatres (resources) and the process paths. Patient Pathways There are four main streams of patients that flow through the theatres. These are identified by the NHS standard Codes termed Intended Management. These are reduced to three in this study because one category constitutes less than 1% of total cases. More appropriate classification of patients termed “Short Stay” and “Inpatients” are presented below; Theatre Load Distribution and Patient Categories The theatre load distribution was analysed from the theatre data in order to decide how to distribute entities (patients) into various theatres. This analysis showed that theatre 1 processes the highest value of 25.94% of patients whilst theatre 7 has the least load of 1.2% of total cases. Four main patient categories are distinguished based on their intended management codes. These are; Day care Short Stay Inpatients Emergency (has the highest priority) For the purposes of this project, another form of patient classification was introduced based on the duration of operation. This produced the patient classes named Minor, Major or Major +, Intermediate, Complex major. The detail of this classification is excluded from the volume in this paper. Technical approach This simulation work was accomplished using the Arena Simulation Software from Rockwell Automation. The model comprises all activities between when a patient leaves the ward to the theatres and when he or she returns to the ward after recovery. It however does not include the details of any activities that take place within the wards. This section briefly describes the various parts of the department that have been included in the model. Transfer control room This is the first point of call for all patients except day cases. Read More