Authors: Edina Erdei, József Popp, Judit Oláh
Title: COMPARISON OF TIME-ORIENTED METHODS TO CHECK MANUFACTURING ACTIVITIES AND AN EXAMINATION OF THEIR EFFICIENCY
Keywords: process system manufacturing, PERT analysis, CPM method, automation, economic impact
Background: Warehouse Production management systems now require IT aspects which can be automated, so that processes can be easily reviewed. During our research, we analyzed four and a half years of database and machine stock of 3 food companies. We have found that companies in this industry prefer process-based production. It is important that manufacturing companies pay close attention to the proper design of automation, the purpose of which is to acquire and maintain a competitive advantage through the efficient, rapid manufacture of products. The expansion of industrial robots has increased considerably (Figure 4.), increasing the productivity, accuracy and flexibility of manufacturing processes, and has enabled a number of business processes to be re-established and new business models brought to life.
Methods: The two best time-oriented methods, the PERT and CPM analysis, were used to assess the individual stages of the production, which made estimates for the duration of the activities. When drawing the box graph, we extracted outlying data from the data set, so we obtained a more accurate statistical estimate. Using this, we made a recommendation for the expected completion of workflows, which is more accurate in determining delivery dates for sales orders. Analyzing the four-and-a-half year dataset, we determined, by using Student's t-test, that the average of the sample elements in reality is different from the estimates we made. The PERT and CPM methods have proven themselves in the past decades and continue to be of great value. The ever-changing business world and the high cost have an impact on the economy.
Results: The production times of individual companies are influenced by the use of more modern machines and well-developed manufacturing plans and schedules. Using PERT and CPM methods, we've helped to better define production time, making it easier to calculate delivery dates correctly. Automation does not stop all occupations, but only triggers certain activities and redefines jobs. There is no doubt that the technological development of manufacturing processes will change the organization of the industries concerned and affect the geographic location of each activity. There is a serious chance that the production of these products will go elsewhere to save on shipping costs.
Conclusions: During our analysis, we have found that new technologies have an impact on productivity, employment and the transformation of the geographic structure of value-added activities, that’s why their role is important both for food companies and companies operating in other industries. Automation is made possible by scientific achievements and technological advances that are used to develop industry 4.0 technologies. The huge amount of data produced in the Intelligent Production Systems (Big Data) analysis and on this basis, the continuous modification of production systems, results in significant material and labor saving, efficiency gains and productivity gains, which have an impact on employment and the transformation of geographic structures. Food processing and delivery to consumers is a key factor in the security of food supply, and therefore has an essential importance in the further development of the sector.
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|MLA||Erdei, Edina, et al. "Comparison of time-oriented methods to check manufacturing activities and an examination of their efficiency ." Logforum 14.3 (2018): 8. DOI: 10.17270/J.LOG.2018.290|
|APA||Edina Erdei, József Popp, Judit Oláh (2018). Comparison of time-oriented methods to check manufacturing activities and an examination of their efficiency . Logforum 14 (3), 8. DOI: 10.17270/J.LOG.2018.290|
|ISO 690||ERDEI, Edina, POPP, József, OLáH, Judit. Comparison of time-oriented methods to check manufacturing activities and an examination of their efficiency . Logforum, 2018, 14.3: 8. DOI: 10.17270/J.LOG.2018.290|