Management is the process carried out to effectively deal with the things or peoples or effectively control the peoples. This process contains the process of developing the plan or strategy, establishing the developed plan successfully and also allocating the various resources effectively to achieve the objective of the organization. In the industry, there are many kinds of management practices followed. Among them, operation management is the important one (Bhadur, 2008). The combination of machine, manpower and material analysis will be done in the operation management (Hauge and Paige, 2004). This analysis is used for the verification and decision making. The system delivers the important resources for the production as output. These results deliver the data gathering before the determination of resource allocation. The managers in the production fields are used to make the resource allocation in an effective way (Ghadimi, Kara, and Kornfeld, 2015). This system also merges the RFID and AI techniques for establishing the result verification. And it concludes in the way of results of the fuzzy logic for the resource allocation and it could be responsive and adaptive for the normal production.
In order to achieve the operation management plan for the production industry, the following things need to be done. And they are known as key objectives of the project.
According to the research carried out by ‘Lee, C et al.,’ in the resource allocation for manufacturing systems focuses on effective resource allocation, this paper uses the intelligent data management. This system contains material and data for making effectiveness in the production field. And for the analysis of effectiveness, it combines the fuzzy logic and database management system. (Lee et al., 2014).
According to the research carried out by ‘Katrin Oettmeier’ on adoption of manufacturing technology for supply chain management process and components, this paper delivers the systematic analysis of the effects of the supply chain management system and their components. And here the analysis is made on components of SCM and adoption of AM technology. Many factors are described to explain the effects of a system. Here in the paper, some manufacturing components are induced to make a concern about the supply chain management process. The research is made for analyzing the supply chain management system and adoption of manufacturing technology (Oettmeier and Hofmann, 2016).
According to the research carried out by ‘Ifeyinwa Juliet Orji’ on dynamic modeling of sustainable operation, the purpose of this paper is to provide the analysis, sustainable operation of dynamic modeling. Here the results are compared by using the decision-making model (Orji and Wei, 2015).
According to the research carried out by ‘Pushkar Shelar’ on the implementation of operating management strategies in manufacturing companies, The techniques involved in the operation management are needed in the manufacturing field. In the organization, various kinds of system and processes are used in the manufacturing department. The research is going for process and techniques of the operation management. This paper aims to do research on existing research paper. This research is based on the scope of the operations management techniques. The analysis of operation management has some disciplines. They are ERP, TOC, and VAE. And an effort is needed to analyze the integration approach and the logical development (Shelar, 2016).
According to the research carried out by ‘Hanbin Luo’ on the application of ontology in emergency plan management for metro operation, the emergency plans leads the main role in the metro operation in this paper. The ontology-based management is used here for providing the best plans for the metro operation. The emergency plans are used to integrate the Ontology-based plan repository for metro operation (Luo, Peng, and Zhong, 2016).
In manufacturing industries, the importance of the operation management plan is too high. The overall efficiency of the process depends on the operation management plan. And the various scopes of the operation management plan are described below (Bisen and Srivastava, 2009).
These are the main assumptions considered for this project. Other than these assumptions some other assumptions are also considered. But the listed things are the key assumptions (Han and Du, 2011) (Lee et al., 2014).
At first, all the relevant details are collected in developing the operation management plan for the production company (Lin et al., 2016). It involved in the collection of the various details like the number of machine tools available, set of resources available etc. After collecting the various details of the operation management plan development, the outline of the production cells are needed to be developed (Christine and Prinsloo, 2015). Because of this process gives better control over the process. After cell development the cells are organized in the proper manner. The various machining processes carried out in the cells are found and assigned (Luo, Peng and Zhong, 2016). In this project there are three major cells. And they are classified based on the component they produce. In the model the cell one was a cell which produces the cylinder assembly required for the air pump. In this section there are some subparts (Mohammadi-Ivatloo and Jabari, n.d.). Similarly the second cell to be grouped to produce the piston and its assembly (Support.simul8.com, 2018). Then the cell three was responsible for producing the body of the pump. All the cells are equipped with the machineries required for the analysis.
These details are fed into the model developed by using the simple 8 software. Schematic layout of the developed model in simulation is shown here.
Figure 1 Schematic lay out of the developed Operation management plan
During the operation, it needs the tools and techniques for analyzing the suppliers in the manufacturing environment (Oettmeier and Hofmann, 2016). This behavior is analyzed by using the approach such as system dynamics. The challenges in the operations are solved by using the fuzzy logic. In the design approach, it uses the Technique such as SD simulation. The result of this operation could be reliable. The simulation process is categorized into four scenarios (Orji and Wei, 2015). They are past, current, future and average time. The plans could be a plain text document and they are used to make the documentation and maintenance. Here the operation plans such as rapid knowledge retrieval and acquisition provide the poor performance in operation (MBA Crystal Ball, 2018) (Russell and Taylor, 2000). And here added the knowledge in the way of text is used to make the recovery of emergency plans.
After completing the simulations of the developed model through the simple 8 simulation software the following things are found. And they are described in the below context (Shelar, 2016).
Figure 2 Review of Results.
In the above diagram, the overall review of the developed model’s performance was given. In this figure the various results are plotted as the graph. For example, the overall work to the time was plotted on the image. From the image, it is noticed that the work output increased with the increase of time.
The below image gives details about the end time of the system. Here the average time taken for the process as well as the best time limit for the process and the worst time taken for the process was shown.
Figure 3 Time taken for Completion of the work
The Income statement is the statement of the developed model, it consists of the details about the various costs and the revenue of the process. It contains the cost consumed for each individual process in the process. The cost sheet calculated from the simulation is attached here.
In the below images the working as well as the waiting times for the various process was shown. Based on this image we may know about the effectiveness of the various processes. And its impact on the performance was calculated by using this document.
Figure 4Relation between the Working time and the Waiting time
The various emissions are involved in the production process. Among them, the CO2 emission is the important factor. And the CO2 emission for the developed model is attached here.
The developed simulation model is attached here.
The role of operation management is to monitor the transforming process. In the manufacturing, the operation manager has some roles (Simul8.com, 2018). They are planning for the production, production control, and the quality control. During production planning, the managers need to consider how goods will be produced in the production process and need to make a concern about site selection. They mainly need to consider the layout of the planning. For the selection in the production process, the manager needs to consider about three methods. They are made to order strategy, mass production, and mass customization. The manager needs to analyze the goods related to the customer specification. Then need to consider the high volume of goods. Finally, they need to check the customization. Then the managers need to monitor the location for the manufacturing operations. And it could be shipping costs. The managers need to make the concern about the skilled workers and their families and they need to provide the offer in the way of low cost and needs to have a supportive business climate. Then the managers need to estimate the product quantity and also calculate the required capacity of the production facility.
In the previous section, the major role of the operation management plan in the manufacturing or production industry was explained in detail. Here the key significance of the operation management plan is described. And they are listed below.
Conclusion
In this project the operation management concepts and their significance in the manufacturing process was studied. Then the various previous works related to the operation management plan development as well as simulation were studied. Then the outline of the problem was developed using the initial details collected. And for the requirement, assumptions were made for the operation management plan. Then the operation management plan (Simulation model) was developed using the simul 8 software tool. The resources were allocated for the development model. Finally, the simulation was carried out using the same software itself. From the simulation process, various key outputs of the developed model were found. These parameters are used to assist the decision making during the implementation of the developed operation management plan. The results were generated from the simulation process. In this paper, the income and expenditure of the plant as well as the carbon emissions and the kpi history of the plan was generated. These details are very important during the decision making process.
References
Bhadur, R. (2008). Production and operation management. Jaipur, India: Book Enclave.
Bisen, V. and Srivastava, S. (2009). Production & operation management. Lucknow, India: Word-Press.
Christine, M. and Prinsloo, M. (2015). Authenticity in marketing: a response to consumer resistance?. Journal of Marketing and Consumer Behaviour in Emerging Markets, 2015(2), pp.15-32.
Ghadimi, P., Kara, S. and Kornfeld, B. (2015). Real-Time Operation Management of CHP System in Manufacturing Industry. Modern Applied Science, 9(2).
Han, L. and Du, R. (2011). Study on Operation Management of Producing Service Company for Manufacturing Enterprise. Advanced Materials Research, 201-203, pp.1050-1053.
Hauge, J. and Paige, K. (2004). Learning SIMUL 8. Bellingham, WA: PlainVu.
Lee, C., Choy, K., Law, K. and Ho, G. (2014). Application of intelligent data management in resource allocation for effective operation of manufacturing systems. Journal of Manufacturing Systems, 33(3), pp.412-422.
Lin, Y., Chen, Y., Huang, W. and Hong, C. (2016). Development of BIM Execution Plan for BIM Model Management during the Pre-Operation Phase: A Case Study. Buildings, 6(1), p.8.
Luo, H., Peng, X. and Zhong, B. (2016). Application of Ontology in Emergency Plan Management of Metro Operation. Procedia Engineering, 164, pp.158-165.
MBA Crystal Ball. (2018). Production and Operations Management | MBA Crystal Ball. [online] Available at: https://www.mbacrystalball.com/blog/operations-management/ [Accessed 2 Aug. 2018].
Mohammadi-Ivatloo, B. and Jabari, F. (n.d.). Operation, planning, and analysis of energy storage systems in smart energy hubs.
Oettmeier, K. and Hofmann, E. (2016). Impact of additive manufacturing technology adoption on supply chain management processes and components. Journal of Manufacturing Technology Management, 27(7), pp.944-968.
Orji, I. and Wei, S. (2015). Dynamic modeling of sustainable operation in green manufacturing environment. Journal of Manufacturing Technology Management, 26(8), pp.1201-1217.
Russell, R. and Taylor, B. (2000). Operations management. Upper Saddle River, N.J.: Prentice Hall.
Shelar, P. (2016). Operation Management Strategies Implemented in Manufacturing Companies: Review of Literature. We’Ken- International Journal of Basic and Applied Sciences, 1(3).
Simul8.com. (2018). Tutorials [SIMUL8 Resource Center]. [online] Available at: https://www.simul8.com/support/help/doku.php?id=tutorials [Accessed 2 Aug. 2018].
Support.simul8.com. (2018). Beginner’s Tutorial | SIMUL8 Support Portal. [online] Available at: https://support.simul8.com/category/beginnerstutorial/ [Accessed 2 Aug. 2018].
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