Multi-criteria decision making in evaluating digital retrofitting solutions: utilising AHP and TOPSIS

Abstract

In an era of digital transformation, evaluating effective strategies for upgrading manufacturing systems is crucial to maintaining competitiveness. Digital retrofitting has become a strategic approach integrating new digital technologies into legacy systems to share data and align with Industry 4.0 principles. However, various techniques and criteria exist for implementing digital retrofitting. Despite its importance, there is a notable lack of studies assessing these retrofitting approaches using multi-criteria decision making (MCDM) methodologies. This study addresses this gap by employing two MCDM techniques: the analytic hierarchy process (AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS). It assesses three digital retrofitting alternatives, starter kit solutions, embedded gateway solutions, and IoT hardware-based solutions, against ten critical criteria. These criteria were weighted through pairwise comparison analysis based on a survey of twelve industry practitioners to reflect industry preferences. The aim is to determine the most effective digital retrofitting approach to aid manufacturers in transitioning to Industry 4.0. This study addresses the complexities of managing conflicting criteria in digital transformation. Moreover, the results contribute to decision-making methodologies by demonstrating their practical applications, thus guiding manufacturers through the intricate landscape of digital retrofitting.