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Innovative managerial control system (IMCS): an application in precast concrete building products industry

机译:创新管理控制系统(IMCS):在预制混凝土建筑产品行业中的应用

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摘要

The monitoring and control of business processes and their variables have strategic importance in order to respond to the dynamics of the world of business. Many monitoring processes are focussed on controlling time and cost and the overall performance is evaluated through a standard set of key performance indicators. These passive approaches do not consider a holistic/system view and therefore ignore the interrelationships between various external and internal variables impacting a business process. This paper investigates an application of multivariate statistical process control techniques [mainly principal component analysis (PCA) and partial least squares (PLS)] which have been successfully used in process and chemical industries, to model, monitor, control and predict business process variables. A prototype, innovative managerial control system (IMCS), was developed to investigate the application of PCA and PLS techniques to monitor, control and predict business process performance. Data was collected and analysed using a case study in a precast concrete building products company. This study has proved that the PCA approach can be effectively used to control business processes. Also, the PLS approach is found to provide better forecasts as compared to commonly used decomposition method. The benefits and limitations of using multivariate statistical process control techniques as applied to business process control are highlighted.
机译:监视和控制业务流程及其变量具有战略重要性,以应对业务环境的动态变化。许多监视过程集中于控制时间和成本,并且通过一组标准的关键绩效指标来评估整体绩效。这些被动方法没有考虑整体/系统视图,因此忽略了影响业务流程的各种外部和内部变量之间的相互关系。本文研究了已在过程和化学工业中成功使用的多元统计过程控制技术[主要是主成分分析(PCA)和偏最小二乘(PLS)]的应用,以建模,监视,控制和预测业务过程变量。开发了原型创新管理控制系统(IMCS),以研究PCA和PLS技术在监视,控制和预测业务流程绩效中的应用。使用预制混凝土建筑产品公司的案例研究收集和分析数据。这项研究证明了PCA方法可以有效地用于控制业务流程。此外,与常用的分解方法相比,PLS方法还可以提供更好的预测。强调了将多元统计过程控制技术应用于业务过程控制的好处和局限性。

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