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Application of the quick scan audit methodology in an industrial filter production process

机译:快速扫描审计方法在工业过滤生产过程中的应用

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The quick scan audit methodology (QSAM) is an established investigative tool to assess the health of business processes and supply chains within short schedules. This study extends the standard QSAM procedure to include the simulation step. It also extends the QSAM to a wider industry platform by applying it into the precision mechanical engineering industry, where managers have been under competitive pressure to reduce an industrial filter production lead time. Following a review of the relevant literature, this paper presents the research design adopted in the study. The QSAM has been conducted using various data collection techniques (such as observations, process activity mapping, interviews, questionnaires, brainstorming and access to company documents) and data analysis methods (including cause and effect analysis, Pareto analysis and time series plot). This is followed by the development of a set of improvement strategies, namely, direct information sharing, priority planning, and additional data recording and analysis. In addition to testing the potential benefits of changing scheduling approaches for the paint plant, simulation has been utilized in this study as a communication means to increase employee participation in the QSAM process and enhance the audit accuracy. It has also provided the case company with a better understanding of the behaviour and characteristics of the system under study, thus facilitating more thoughtful decisions to improve the system. The paper concludes with further research opportunities derived from this study.
机译:快速扫描审计方法(QSAM)是一个建立的调查工具,以评估业务流程的健康和供应链在短期内。本研究扩展了标准QSAM程序以包括模拟步骤。它还通过将QSAM延伸到更广泛的工业平台,将管理人员延伸到更广泛的机械工程行业,管理人员在竞争压力下降低工业过滤生产延期时间。在审查相关文献之后,本文提出了研究中采用的研究设计。 QSAM已经使用各种数据收集技术(例如观察,过程活动映射,访谈,调查表,头脑风暴和公司文件访问)和数据分析方法(包括原因和效果分析,帕累托分析和时间序列图)。这是开发一套改进策略,即直接信息共享,优先级规划和附加数据记录和分析。除了测试改变涂料植物的调度方法的潜在好处之外,本研究中已经利用了模拟,以增加员工参与QSAM过程并增强审计准确性。它还提供了案例公司,更好地了解所研究中系统的行为和特征,从而促进了更加周到的决定改善系统。本文得出结论,源自本研究的进一步研究机会。

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