Epsilon Archive for Student Projects

Abstract

Today, we are standing on the brink of the fourth industrial revolution, called Industry 4.0. This new era has developed from combining new technologies into the manufacturing system, such as artificial intelligence, additive printing, and cyber-physical systems. As one of the largest industries in Sweden, and the fifth largest producer of wooden products globally, operating in one of the most eminent technological countries, one might assume that the Swedish forest industry would be at the forefront of this evolution in the industry. However, due to segregated digital supply chains and a lack of knowledge about the concept, manufacturers struggle to implement a strategy towards the concept. Nevertheless, it does exist an interest in adapting the concept of Industry 4.0 into the industry.
One of the key impacts that Industry 4.0 will have on manufacturing systems is the availability of real-time information through the entire value network, allowing decision-making on reality rather than assumptions. It is therefore evident that Industry 4.0 will have a significant impact on operational decision-making, including scheduling. Scheduling manufacturing systems concerns the operational decision-making deciding on “when” to produce the product. Further, scheduling in sawmilling is complex, building on experience and information from several different processes.
With this background, it became evident that further research regarding processes' ability to support operational decision-making in Industry 4.0 was needed. Therefore, the purpose of this study was to outline the potential of Industry 4.0 for operational scheduling in the sawmill industry. The intent is to explore improvements in the processes' ability to support operational decision-making in Industry 4.0.
Information gaps between the scheduler and the processes were mapped using a single-case study, collecting data through participant observations and interviews. Processes in direct contact were evaluated based on their ability to support operational decision-making in Industry 4.0 by using the “Acatech Industrie 4.0 maturity Index”.
The results showed that the processes possessed varying abilities to support operational decision-making. Therefore, a four-step roadmap was constructed to improve its processes' ability to support operational decision-making. In the initial stage were improvements of digital capability and integration between the processes and the scheduler recommended. The lacking information about the logs constitution disrupted the scheduler's ability to forecast product output, which resulted in re-scheduling in the following processes. Additionally, improving the processes’ ability to visualize relevant data to the scheduler could improve the trustworthiness of the manufacturing system.