Mathematical Modelling Designed for Monitoring Traceability and Quality Statistical Control in Romanian SMEs

Raul Bogdan Mircea, R. Lile, D. Ţucu, L. Gal, T. Babanatsas
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Abstract

Abstract The paper presents a confirmed case of a factory in the west of the country, where the stochastic modeling generated by the software was implemented into SAP. This project was born out of necessity. Thus, to keep the processes under control and contribute to their improvement, they must be monitored, measured and analyzed regularly. As long as the main process indicators are monitored, the need to take corrective or improvement actions (whether reorganization or additional investment is needed) can be detected in time so that the company’s performance does not decrease to the level where the customer is no longer satisfied of the quality of the delivered products or too high non-quality costs appear that will no longer allow the achievement of the established objectives (Besterfield, D. H. et al., 2011). The program is presented in detail, starting with the introduction of collected data, the processing and generation of indicator graphs. The indicators have high accuracy and greatly help in making decisions. Finally, an improvement in production can be observed following the use of this software (Bourne, M., & Bourne, P., 2012). The purpose of our study is to create a stochastic mathematical model. Starting from a specific condition in SMEs from Romania, this study presents possibilities of innovation in operational structures specialized in quality monitoring, traceability and statistical control based on integrated modules in general software. The innovation process is based on data collected and monitored in real-time from the manufacturing process in conditions where the system ensures quality compliance at all stages of production. Through its modern functionalities, blockages are eliminated, waste of time is avoided, materials and money are saved, and it strengthens the business partnerships and the company’s position in the market. Results regarding particular implementations are preserved. Data is collected and monitored in real-time and the system ensures quality compliance at all stages of production.
为罗马尼亚中小企业监测可追溯性和质量统计控制设计的数学模型
摘要本文以西部某工厂为实例,将软件生成的随机建模应用到SAP中,该项目应运而生。因此,为了使过程处于控制之下并有助于其改进,必须定期对其进行监视、测量和分析。只要对主要过程指标进行监控,就可以及时发现需要采取纠正或改进措施(无论是重组还是需要额外投资),从而使公司的绩效不会下降到客户不再满意交付产品的质量或出现过高的非质量成本,从而不再允许实现既定目标的水平(Besterfield, d.h. et al., 2011)。从采集数据的介绍、指标图的处理和生成等方面详细介绍了该程序。这些指标具有较高的准确性,对决策有很大的帮助。最后,在使用该软件后,可以观察到生产的改善(Bourne, M., & Bourne, P., 2012)。我们研究的目的是建立一个随机数学模型。从罗马尼亚中小企业的具体情况出发,本研究提出了基于通用软件集成模块的质量监测、可追溯性和统计控制的业务结构创新的可能性。创新过程基于从制造过程中收集和实时监控的数据,系统确保在生产的所有阶段都符合质量要求。通过其现代化的功能,消除了阻塞,避免了浪费时间,节省了材料和金钱,并加强了业务伙伴关系和公司在市场中的地位。保留有关特定实现的结果。该系统实时收集和监控数据,确保生产各个阶段的质量符合要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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