Use of Key Performance Indicators in Production Management

Improving production performance requires the definition of global production objectives with a proper implementation strategy and suitable closed-loop control for their achievement. Closed-loop control structures for simple systems like temperature or velocity control are well defined, but a synthesis of plant-wide control structures is still recognised as the most crucial production management design problem in process industries. One vital issue to be resolved is how to translate implicit operating objectives, such as the minimisation of production costs into a set of measurable variables that can be then used in a feedback-control. A promising solution is the use of the key performance indicator (KPI) approach. To verify the idea of production feedback control using production KPIs as referenced controlled variables, a procedural model of a production process for a polymerisation plant has been developed. The model has been used during a number of simulation runs performed with the aim of developing and verifying the idea of KPI-based production control

[1]  Sigurd Skogestad,et al.  Self-optimizing control: the missing link between steady-state optimization and control , 2000 .

[2]  Vladimir Jovan,et al.  Integration of Business and Production Levels in Process Industries , 1998 .

[3]  Knut Holt,et al.  Management and organization through 100 years , 1999 .

[4]  Gerald K. Debusk,et al.  Components and relative weights in utilization of dashboard measurement systems like the Balanced Scorecard , 2003 .

[5]  R. Kaplan,et al.  The Balanced Scorecard: Translating Strategy into Action , 1996 .

[6]  Nasreddin Dhafr,et al.  Establishing and improving manufacturing performance measures , 2002 .

[7]  George Stephanopoulos,et al.  Perspectives on the synthesis of plant-wide control structures , 2000 .

[8]  Management ™ are Trademarks of SAP AG. The Management Cockpit ™ is a Trademark of SAP AG, originally created by Prof. , 2022 .

[9]  Wilhelm Dangelmaier,et al.  Virtual and augmented reality support for discrete manufacturing system simulation , 2005, Comput. Ind..

[10]  T. T. Mirnalinee,et al.  Computers in manufacturing: towards successful implementation of integrated automation system , 2005 .

[11]  Fabrizio Salvador,et al.  Information flows for high performance manufacturing , 2001 .

[12]  Marc Wouters,et al.  Designing a performance measurement system: A case study , 2004, Eur. J. Oper. Res..

[13]  Thomas F. Edgar Control and operations: When does controllability equal profitability? , 2003 .

[14]  Karsten P. Ulland,et al.  Vii. References , 2022 .

[15]  Eric Scherer Approaches to Complexity and Uncertainty of Scheduling in Process Industries: Process Regulation in Highly Automated Systems , 1995 .

[16]  R. Kaplan,et al.  The balanced scorecard--measures that drive performance. , 2015, Harvard business review.

[17]  Sigurd Skogestad,et al.  Control structure design for complete chemical plants , 2004, Comput. Chem. Eng..

[18]  Carlos Andrés,et al.  A design and application methodology for hierarchical production planning decision support systems in an enterprise integration context , 2001 .