Published Apr 11, 2018
Ilker Topcu Berna Unver Mine Isik Ozgur Kabak


Due to product variety and modeling structure, the automotive manufacturing process requires state-of-the art production methods that cause a high complexity level in operations which assembly operators work in a mixed-assembly environment. To maintain a competitive advantage, companies should take a different approach that considers the methodologies which ensure excellence in operations. This study aims to identify and prioritize potential risk factors that cause errors and failures by applying the Analytic Hierarchy Process to improve the production quality in a manufacturing process of mixed model assembly lines in the automobile industry. Thus, numerous risk factors under three main categories including human-focused, design and process-driven are discussed in this work. The most important contribution of this study is the application of this methodology to find and rank the risk factors based on their importance in a world-leading automotive company in Turkey.

How to Cite

Topcu, I., Unver, B., Isik, M., & Kabak, O. (2018). AN AHP BASED PRIORITIZATION MODEL FOR RISK EVALUATION FACTORS IN THE AUTOMOTIVE INDUSTRY. International Journal of the Analytic Hierarchy Process, 10(1).


Download data is not yet available.
Abstract 1327 | PDF Downloads 272



automotive, assembly line, workstation, process complexity, AHP

Antani, K.R. 2014. A study of the effects of manufacturing complexity on product quality in mixed-model automotive assembly, Doctoral dissertation, Clemson University,

Mattsson, S. & Gullander, P. & Harlin, U., & Bäckstrand, G. & Fasth, A. & Davidsson, A., 2012. Testing complexity index – a method for measuring perceived production complexity, 45th CIRP Conference on Manufacturing Systems, 3, 394-399. Doi:

Personne, R. & Matinlassi, V., 2014. Part assurance in a mixed-model assemble line, Master of Science Thesis.

Saaty, T.L. (1980) Multicriteria decision-making: The analytic hierarchy process. Pittsburgh, PA: RWS Publications.

Super Decisions, 2018,

Urrutia, U.A. & Webb, P. & Summers, M., 2014. Analysis of design for X methodologies for vomplex assembly processes : A literature review, ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 1-11. Doi: doi:10.1115/DETC2014-34955

Zeltzer, L. & Limeré, V. & Landeghem, H.V. & Aghezzaf, E. & Stahre, J., 2013. Measuring complexity in mixed-model assembly workstations, International Journal of Production Research, 51(15), 4630-4643. Doi:

Zhu, X. & Hu, J.S. & Koren, Y. & Marin, P.S., 2008. Modeling of manufacturing complexity in mixed-model assembly lines, Journal of Manufacturing Science and Engineering, 130, 1-10. Doi: 10.1115/1.2953076