Vehicle Exhausts Emission Pattern Decisions for Logistic Services and Packing Industries with Orthogonal Array-Based Rough Set Theory


  • Alexander Iwodi Agada Department of Mechanical Engineering, University of Lagos, Lagos, Nigeria
  • Sunday Ayoola Oke University of Lagos, Lagos, Nigeria
  • John Rajan Department of Manufacturing Engineering, School of Mechanical Engineering, Vellore Institute of Technology, Vellore, India
  • Swaminathan Jose School of Mechanical Engineering, Vellore Institute of Technology, Vellore, India
  • Pandiaraj Benrajesh Dexterity Design Services, Chennai, India
  • Elkanah Olaosebikan Oyetunji Department of Mechanical Engineering, Lagos State University, Epe Campus, Nigeria
  • Kasali Aderinmoye Adedeji Department of Mechanical Engineering, Lagos State University, Epe Campus, Nigeria



emission, decision making, developing country, approximations


Precise monitoring of vehicle emissions in green logistics, focusing on the contributions of vehicles from packing industries, is crucial for many issues. It helps to understand the total emissions and gain insights into the mechanism of vehicle-associated environmental concerns. Notwithstanding, a key issue when monitoring vehicle emissions is the effective discrimination problem for different patterns generated from the parameters. Data from the packing industry are available from distribution networks but its pattern cannot be discriminated. Given this background, this article presents a new method of the orthogonal array-based rough set to discern patterns of the parametric behaviors to monitor emissions from vehicle exhausts in the packing industry. The proposed method is based on an Indian logistics network and delivery system data, which was obtained from previous work in the literature. By setting controls on the parameters of the packing industry which includes revenue obtained, packing units sold, growth rate, carbon-dioxide equivalent, materials utilized, and quantity consumed, the method was able to discern the patterns of the parametric behavior. The orthogonal arrays, which are developed, form factors (parameters) and levels to ascertain a balanced and uniform analysis of the various groups of options. Indiscernibility and approximation concepts of fuzzy sets are then applied to arrive at the outcome. Unlike previous studies, this study eliminates the need for tracking data, assumptions, and external information to establish the set membership. However, it utilizes the available information within the data. The rough set analysis indicates that there are no discernable patterns or rules that distinguish between "Yes" and "No" decisions. The method of rough set illustrated in this work shows the feasibility of the approach in the Indian packing industry. The method is useful for the logistics manager and government agencies responsible for the control of vehicle-generated greenhouse emissions.

Author Biographies

Alexander Iwodi Agada, Department of Mechanical Engineering, University of Lagos, Lagos, Nigeria


John Rajan, Department of Manufacturing Engineering, School of Mechanical Engineering, Vellore Institute of Technology, Vellore, India


Elkanah Olaosebikan Oyetunji, Department of Mechanical Engineering, Lagos State University, Epe Campus, Nigeria


Kasali Aderinmoye Adedeji, Department of Mechanical Engineering, Lagos State University, Epe Campus, Nigeria



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How to Cite

Agada, A. I. ., Oke, S. A., Rajan, J. ., Jose, S. ., Benrajesh, P. ., Oyetunji, E. O. ., & Adedeji, K. A. . (2023). Vehicle Exhausts Emission Pattern Decisions for Logistic Services and Packing Industries with Orthogonal Array-Based Rough Set Theory . International Journal of Industrial Engineering and Engineering Management, 5(2), 97–106.