Search results

This study aims to introduce the model of implementation to run the smart production factories. The study also aims to investigate the Industry 4.0 technologies as enablers to deal with challenges in the way of implementation.

This contribution benefits from two teams of experts to evaluate the challenges and technologies of Industry 4.0. The Hanlon method is applied to evaluate, rank and prioritise the challenges which are initially scored by experts’ Team 1. Then, the adjacency matrix among enablers and challenges is extracted through the opinions of experts’ Team 2. The study also uses fuzzy cognitive map (FCM) to evaluate the real weights of technologies and challenges, rank and prioritise subsequently.

A total of 8 challenging obstacles and 24 key technologies have been evaluated. The findings reveals that recruit and retention of experienced managers, undefined return on investment and recruit and retention of multi-skilled workers are the most serious challenges in the way of implementing smart production factories. Furthermore, big data, IT-based management and Internet of Things are the top-ranked key enablers to face the challenges.

To the best of the authors’ knowledge, this study is one of the pioneering studies that uses Hanlon method to evaluate industrial challenges. Integrating Hanlon method and FCM leads to a comprehensive model of evaluation and ranking which is another novelty of this contribution. Although many research studies have been released to implement the smart factories, practical model of implementation for production factories is identified as a literature gap.