Conference Agenda

In business process reengineering, engineering approaches to realize effective business processes have been studied in an interdisciplinary manner involving researchers in management, sociology, and other fields. Predicting design effectiveness, identifying effective design parameters and their settings, and selecting the optimal design are essential to realize effective business processes. Therefore, the objective of this paper is to demonstrate that the method with agent-based models and simulation can assist designers' decision-making and provide necessary knowledge through a case study of business process design for both cyclic and acyclic demand fluctuations. The case study was conducted on an IT systems department business process of a company that processes 50 demands with different demand fluctuation types. The simulation model described the demands and corresponding operations in a hierarchical manner to reduce the complexity of the design description. 16 design scenarios were prepared by combining 4 design parameters. The case study examined the problems of how the proposed method could provide knowledge regarding selection of optimal design scenarios, effective design parameters and their settings, and causal relationships of design parameter changes and effects. The case study results confirmed that our proposed method can provide useful knowledge. For example, that two specific design parameters have a synergistic effect, and that the effect of changing the design parameter of teaming is not caused by teaming itself, but the communication-work reduction that results from teaming, were provided. The results demonstrated that the proposed method could assist designers' decision-making and provide them with necessary knowledge in designing business processes.

With the recent surge in e-commerce, logistics demand has soared, causing driver shortages and reduced transport efficiency. Addressing these challenges requires proactive measures not only from delivery services but also from shippers. Traditionally, shippers have balanced capital efficiency with inventory management opportunity cost. However, escalating transportation costs and increasing environmental regulations are compelling shippers to prioritize transport efficiency. This research introduces comprehensive methodologies comprising three key components: firstly, risk calculation based on demand forecasting with machine learning; secondly, the development of strategies focused on balancing opportunity loss, capital efficiency, and transportation efficiency; and thirdly, the implementation of transportation bundling to optimize transportation efficiency. A case study was conducted involving an e-commerce company to validate these methods. The case study demonstrates the effectiveness of the proposed approach in reducing total costs and the importance of aligning strategies with product characteristics. It also shows how transportation bundling increases load efficiency. The study introduces a risk calculation methodology linked to demand forecasting. It also suggests transportation bundling to increase efficiency. Furthermore, it shows that these methods can effectively balance the trade-offs that shippers face in inventory management, specifically between opportunity cost, capital efficiency, and transport efficiency.

System endurance characterises how long the system can remain operational without requiring external interference. This concept is particularly important for mission critical systems, where an essential requirement is to stay on mission as long as feasible. The conventional engineering approach focuses on technological advancement and innovative design to increase operation cycles. However, this does not always translate successfully to reality. Over the last century, submarine design changed from diesel power to nuclear propulsion systems. Contemporary submarines theoretically have almost unlimited endurance - they can stay on mission (remain submerged) for years. As this type of system costs billions, it is essential to have clear direction for maximising capability outcome against cost. This research takes a transdisciplinary approach, extending system analysis to much broader perspectives by applying 3PE modelling to assess the endurance of submarines through historical developments. The analysis found “Product” elements such as hull form and power generation have improved tremendously. The “Process” elements have correspondingly adapted to ensure proper operation of the “Product”. However, the “People” elements do not exhibit any recognisable change. In fact, as submarines increase in size, more personnel are required to handle system tasks. Clearly endurance of some parts of the system have been mitigated by design/technology advancements, but other parts within the system remain under-performed. The 3PE framework analysis raises questions including, can these limiting factors be designed out with emerging technologies such as AI? This paper demonstrates a prognostic assessment of where effort should be applied, to achieve advancements in system endurance.

Inventory disposal has become a significant global issue, highlighting the critical role of inventory management, sales forecasting, and subsequent production decisions. In practice, determining the order timing is crucial, considering lead time and the order process. Additionally, feedback from the person responsible for ordering is essential for improving the forecasting method. This study conducted a demonstration experiment testing a new sales forecasting method for newly released products, incorporating practitioner knowledge into variables, and utilizing actual order timings. A decision support system for additional production was also implemented. For about nine months, apparel brand order managers utilized the system, providing feedback that suggested directions for model improvement. The forecasting method employed pre-clustering and a regression model. Results from the demonstration experiment confirmed that the proposed method significantly reduced unnecessary additional production compared to decisions solely reliant on the person in charge. The primary contribution of this study lies in its practical demonstration within a real-world industrial setting, where stakeholders actively engaged with the system and provided valuable feedback, guiding further improvements using a transdisciplinary approach.