An Optimization Framework for Operational-Level Resource Composition in an Inclusive Manufacturing System

Abstract

Manufacturing is an essential component of the economy, and globalization further influences it by the driving forces of outsourcing and distributed manufacturing with technological advances. However, the decreasing share in gross domestic product (GDP) and shrinking employment from the manufacturing sector have become concerning matters. Recently, the inclusive manufacturing paradigm has been proposed by concentrating on globally observed economic, environmental, and societal issues. This paper advances the concept of an inclusive manufacturing system (IMS) by developing an optimization-based model to enable resource composition scenarios. The developed model encapsulates an amalgamation of a realistic and complex production system, suppliers, manufacturers, assembly stations, logistics providers, and courier services. The model aims to optimize the cost and emission of manufacturing, assembly, and logistics systems while producing a product. The formulated optimization problem is discrete in nature with binary and integer decision variables and multiple complexities of nonlinear functions. Therefore, evolutionary techniques are exercised as solution approaches to handle the problem's complexity and size. A simulated case example has been designed to envision the inclusive manufacturing system by perceiving a real-life production scenario of labeling conveyor, a customized product engaged for most packaged items. The study reveals that network size influences cost and emission because of competitiveness among service providers to get the order. The result also insights that a significant share of the cost comes from production and assembling activities, whereas transportation services dominate over manufacturing-assembly activities in carbon emission.