Tidspunkt 

18.03.2022 kl. 09.00 - 16.00

Beskrivelse 

Abstract:

Manufacturing is facing difficulty in evolving and meeting reconfigurability needs because of the prevalence of legacy systems that are heterogeneous and inflexible. This PhD project addresses that challenge by developing design principles that are relevant to the real-world industrial context for manufacturing operations management (MOM). The core system of MOM is manufacturing execution system (MES), which is a factory information system, and its principles aim to enable a smart factory. The smart factory is an information technology (IT)-driven enabler for meeting future manufacturing requirements, such as reconfigurability. It has the capacity to solve the customer responsiveness problem by reducing the time to market and supporting product variety.

Intelligent manufacturing methods, such as agent-based approaches, have previously been studied to solve customer responsiveness problems. However, they have all had weak adoption rates in the industry. Current methods for solving customer responsiveness problems require an in-depth analysis of architectures of enterprise information systems, such as MES/MOM, in the Industrial Internet of things (IIoT). The IIoT involves connecting machines and devices to a network, which is crucial for the computer-based automation of manufacturing operations in a factory and its supply chain for enabling reconfigurability in an Industry 4.0 scenario. MES/MOM is a potential centerpiece of an interconnected and interoperable architecture to implement reconfigurable manufacturing systems for distributed manufacturing control.

MES/MOM, based on the ISA 95 standard, has been crucial industrial software for production execution and online management of factory activities for the past two decades. However, enterprises face challenges in deriving the maximum value from MES/MOM due to its low interoperability, low customizability, and monolithic design. In addition, the manufacturing industry is currently unable to effectively use production data due to the prevalence of legacy systems, which are largely unable to share data with MES/MOM.

Using a design science research approach, the thesis develops architectural design recommendations with the support of Unified Modeling Language illustrations. The aim is to develop a next-generation MES/MOM connected to the IIoT. The design is intended to act as a core of a reconfigurable manufacturing enterprise by supporting the smart factory design principles of (1) information transparency, (2) technical assistance, (3) decentralized decision making, and (4) interconnection. The thesis also establishes the relevance of the ISA 95 standard in an Industry 4.0 context, which has been unclear and undocumented, because ISA 95 does not envision the convergence of IT and operational technology that is required for IIoT.

The empirical basis for the PhD project is the companies of the Manufacturing Academy of Denmark (MADE DIGITAL and MADE FAST projects) network. The case companies for the project include three large production companies with global manufacturing footprints, which are trying to leverage their MES/MOM initiatives. The case companies also include two Danish medium-scale IT consulting companies, which provide technology solutions that interact with or are based on MES/MOM. For the empirical foundation of the project, we conducted semi-structured interviews with MES implementation managers of six large companies, and studied the industry needs around MES/MOM through three industrial demonstrators. The industry needs of the MADE companies underpinned the PhD research. Furthermore, the manufacturers’ potential benefits from improving the MES/MOM design were deduced using the example of Aalborg University’s Smart Production Lab and the quality function deployment method (QFD).