Application of ISA95 data models in manufacturing execution systems for lean production

Udo Wozar, Hueseyin Erdogan, Rafał Cupek, Szymon Ziemek


Manufacturing Execution Systems (MES) are service-oriented interfaces that join the world of business transactions with the world of production systems. Nowadays IT systems have to provide very detailed information that is related to an underlying production process and also to actual product. There are a few emerging business models that require accurate and timely production data. This document examines two approaches to database architecture that can be used in Manufacturing Execution Systems (MES). It focuses on the support of the LEAN business model. The main research goal is to  support the flexible access to production data, but the efficiency of database is also very important factor. Authors compare the classical relational database model with the object-oriented one. Considered use cases include the Oracle DB and Oracle Objects applications for MES. Presented object oriented approach follows the ISA95 standard. The practical use cases are based on the production of electronic devices carried out by the company Continental Ingolstadt. Although object oriented databases are not well accepted by the industry due to their low efficiency, the authors show that in the case of LEAN production, the database system based  object-oriented models can be far more convenient than a classical relational database. The main benefits are more flexible data model and highly adjustable MES that can follow changes in the underlying production system. By the case of LEAN manufacturing, authors show that the flexible object oriented database is more efficient solution comparing to the relational database. Moreover such an approach can help to avoid well known big data problems that are common in classical MES.


MES; Manufacturing Execution System; LEAN production; ISA95

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Shipp S.S., Gupta N., Lal B., Scott J.A., Weber C.L., Finnin M.S., Blake M., Newsome S., Thomas S.: Emerging global trends in advanced manufacturing, DTIC Document, 2012.

Blanc P., Demongodin I., Castagna P.: A holonic approach for manufacturing execution system design: An industrial application. Engineering Applications of Artificial Intelligence. Volume 21, Issue 3, April 2008, p. 315÷330.

Cupek R., Erdogan H., Huczała Ł., Wozar U., Ziębiński A.: Agent Based Quality Management in Lean Manufacturing. In Computational Collective Intelligence, Springer 2015, p. 89÷100.

Do N.: Integration of engineering change objects in product data management databases to support engineering change analysis. Comput. Ind. 73, 2015, p. 69÷81. DOI: 10.1016/j.compind.2015.08.002.

Cupek R., Huczała Ł.: OData for service-oriented business applications: Comparative analysis of communication technologies for flexible Service-Oriented IT architectures. IEEE International Conference on Industrial Technology (ICIT), 2015, p. 1538÷1543.

Lee. J et al: Recent advances and trends in predictive manufacturing systems in big data environment. Manufacturing Letters 1.1 (2013), p. 38÷41.

Choudhary A.K., Harding J.A., Tiwari M.K.: Data mining in manufacturing: a review based on the kind of knowledge. Journal of Intelligent Manufacturing, October 2009, Volume 20, Issue 5, p. 501÷521.

Anvari A., Ismail Y., Hojjati S.M.H.: A Study on Total Quality Management and Lean Manufacturing: Through Lean Thinking Approach, 2011.

Alter S.: Information Systems. Pearson, Upper Saddle River 2002.

Oracle Database documentation Library. 12c Release 1 (12.1). 2014.

Bleeker A.: Prozessoptimierung in der Produktion heute. Productivity Management, März 2012, p. 24÷26.

Charantimath P. M.: Total Quality Management. Pearson, 2011.

ANSI/ISA-95.00.01-2010. Enterprise-Control System Integration – Part 1: Models and Terminology. Approved 13 May.

ANSI/ISA-95.00.02-2010. Enterprise-Control System Integration – Part 2: Object Model Attributes. Approved 13 May 2010.

Gerberich T.: Lean oder MES in der Automobilzuliefererindustrie. Gabler, Chemnitz 2010.

Shang Gao S.P.L.: Lean Construction Management – The Toyota Way. Springer, Singapore 2014.