Internet of things and digital transformation (industry 4.0) strategy and benefits for manufacturing firms

Abstract

The world is changing faster than ever before. Previous industrial revolutions happened within an average of hundred years. The first industrial revolution of mechanization happened in the 18th century followed by electrification in the early 20th century and automation happened towards the end of the 20th century as well. Only after a quarter of a century, the last and fourth industrial revolution kicked in. Digitalization is the key trend of the Industry 4.0 revolution. One of the key aspects of digitalization brought by Industry 4.0 is driven by the Internet of Things. Industrial companies are transforming the way they design and maintain their products, solutions, and production capabilities. Consumer requirements became more demanding than ever before. Competition among the manufacturing companies is at its limits and transforms the products to be more complex. Yet, other challenges such as faster time to market, higher quality needs, and regulations and legislation force enterprises to provide new ways of designing, manufacturing, and servicing their end products. Such changes do not happen overnight, the transformation within large organizations are key aspects of their survival. Because of that, firms are collecting lots of information before deciding on their strategies for digital transformation. One key problem in this regard is to decide on either to buy or implement (vertical integration) such technologies objectively and efficiently. Many firms are dependent on a few individuals' decision-making capabilities. However, human decision-making is not objective most times and this could cause issues for the firms to make the best decision. This thesis consists of three published articles that focus on the 4th industrial revolution's effect on digital transformation strategies and benefits for manufacturing firms. As well as providing a strategical roadmap throughout the journey of digital transformation. Multi-criteria decision-making is key for firms to determine the most appropriate solution among a large set of alternatives. To overcome subjective human judgment challenges, the fuzzy multi-criteria decision-making frameworks are introduced in each article. The proposed frameworks aim to help manufacturing firms strategically apply digital transformation. The first article defines a fuzzy framework for the manufacturing firms in their investment decision in the internet of things domain. From the two possibilities of internal make decision vs external buy decision, there are many factors to be considered. The detailed literature review indicates six important criteria for manufacturing firms to consider in their transformation journey decision making. Based on the provided decision criteria, the Type-2 Fuzzy COPRAS method is used as an application of the framework to help manufacturing organizations compare available alternatives and decide for their organizational nature. The suggested framework is tested in an industrial case study and findings are discussed in the paper. The results indicate that digital transformation is preferred to be outsourced due to its complex nature. In the second article, based on the approach provided by the first article, one of the key components of digitalization is applied. The article investigates how the manufacturing firms should decide on which Product Lifecycle Management (PLM) solution to buy from available options based on the enterprise's requirements. In order to identify the key criteria for PLM selection, a detailed literature analysis is conducted. The result of the literature review shows that six very important criteria exist for PLM application selection. Furthermore, to reduce subjective human judgment, the interval-valued Spherical Fuzzy COPRAS method is suggested as an application selection framework. The industrial case study is applied and alternative PLM solutions are ranked for the case-studied manufacturing firms. The results were satisfactory for the decision-making firms and the proposed framework was considered to be successful by them. In the third and last article, based on the findings from the first article and similarly to the second article, an Augmented Reality (AR) application selection framework is proposed. AR applications are taking a key part in the digital transformation of manufacturing firms. The detailed literature review suggests nine very important criteria to be used to compare alternative AR solutions. To reduce subjective human judgment, the Spherical Fuzzy COPRAS multi-criteria decision-making framework is proposed. The suggested method is tested in an illustrative example and findings are shared with sensitivity analysis. As a result, the thesis provides a strategical roadmap for manufacturing firms to apply digital transformation using internet of things concepts in the era of the 4th industrial revolution. Provided fuzzy COPRAS multi-criteria decision-making frameworks help firms to reduce human judgment subjectivity in their decision making. Furthermore, the detailed literature reviews identify the key criteria for selection frameworks to help manufacturing firms to gain time and conduct best in class decision-making.