Optimization approach for the combined planning and control of an agile assembly system for electric vehicles

For some years now, the automotive industry has been challenged by growing market dynamics, shorter product lifecycles and customers' increasing demands for individualization. In order to cope with this development, the automotive assembly needs to adapt quickly to changing demands with a low level of investment in the future. Under the current circumstances, the traditional line assembly for high volume production is reaching its limits in terms of adaptability and scalability. A promising solution to address the current challenges is the concept of the agile assembly. The concept of agile assembly breaks up the rigid linkage of assembly stations and, thus, enables full flexibility in the sequence of assembly operations only limited by the precedence graph. Therefore, the routing of electric vehicles in the agile assembly is based on the availability of resources such as assembly stations and automated guided vehicles that handle the material supply. Further, by transferring the transport function to the vehicle itself, investments for convey or systems are eliminated. This research work presents an optimization approach for the machine scheduling and transportation planning, which derives instructions for electric vehicles, assembly stations as well as automated guided vehicles. For each electric vehicle, an optimized route is calculated, taking into account product-specific precedence graphs and minimizing the overall makespan. In addition, the machine scheduling and transportation planning is integrated into a combined planning and control concept which covers the allocation of resources and the assignment of capabilities of the entire assembly system. The approach is implemented and applied to a practical case of a compact electric vehicle. Thus, the work contributes to the evaluation of agile assembly systems in automotive production

Path Prediction For Efficient Order Release In Matrix-Structured Assembly Systems

Numerous research papers have already demonstrated the theoretical benefits of matrix-structured assembly systems. Nevertheless, such assembly systems have hardly been used in practice so far. The main reason for this, apart from the technical integration, is the complexity of controlling matrix-structured assembly systems. In theory, decentralized, agent-based control architectures have proven to be particularly suitable. However, order release has been largely neglected so far. Accordingly, the authors' previous work includes a conceptual approach for capacity-oriented order release in matrix-structured assembly systems. This previous approach calculates possible paths of an order and their capacity requirements considering both routing and sequence flexibility. Furthermore, by combining the possible paths of released orders with orders to be released and comparing them with the available capacity, the previously suggested approach can systematically carry out capacity-oriented release decisions. However, the NP-hard (NP: non-deterministic polynomial-time) problem arising from the consideration of all possible paths has a negative impact on the scalability and real-time capability of order release. Therefore, the present paper aims to extend the previously developed approach. By determining the most likely paths that a given order will take through the assembly system, the combination possibilities are limited in such a way that the total amount of calculations required to find a suitable order for release is reduced. Doing so, the NP-hardness of the previously developed approach can be circumvented. This work contributes to the practical realization and economic operation of matrix-structured assembly systems. The paper describes the logic of path prediction in detail and evaluates its impact on order release

Evaluation Of An Capacity-oriented, Agent-based Order Release For Matrix-structured Assembly Systems

To address growing challenges in automotive assembly with ever shorter innovation cycles, increasing variant diversity and uncertain market development, innovative concepts for assembly systems are needed. As a response, the concept of matrix-structured assembly system was introduced. Matrix-structured assembly systems break up with the rigid line structure of assembly stations and replace the cycle time-bound and product-specific station assignment of rigid line structure. A major challenge in the design of matrix-structured assembly systems is the assembly control. While certain approaches, mostly decentral and agent-based, are already capable to assign orders to assembly stations based on the availability of production resources, order release as part of the assembly control has been largely neglected. This is because routing and sequence flexibility lead to temporal uncertainty in the prediction of station-specific capacity requirements. Accordingly, the authors' previous work includes a conceptual methodology for capacity-oriented order release in matrix-structured assembly systems. After implementing this methodology, the actual benefit needs to be determined. For this purpose, the present paper suggests and applies a testing strategy based on the fundamentals of successful testing in software development domain. The testing aims to demonstrate the basic functionality of the implemented methodology as well as to compare it with other order release procedures that have been used for simulations in the context of matrix-structured assembly systems so far. It can be shown that the methodology for capacity-oriented order release in matrix-structured assembly systems achieves better adherence to delivery dates and lead times by anticipating bottlenecks compared to ConWIP control with a random order release. The knowledge gained from the testing strategy contributes to the improvement of order release procedures in matrix-structured assembly systems

From Complexity To Clarity In Sustainable Factory Planning: A Conceptual Approach For Data-driven Integration Of Green Factory KPIs In Manufacturing Site Selection

The selection of manufacturing facility locations entails high costs and long-term consequences. This necessitates an objective approach to mitigate uncertainties associated with subjective decision-making. Our paper builds upon previous research on data-driven location selection and conceptually extends it to integrate sustainability potential evaluation. By combining Green Factory Key Performance Indicators (KPIs), the authors aim to facilitate and standardize long-term decision-making in sustainable factory planning. After outlining the requirements, current state of the art, and limitations of location selection, we emphasize the need for integrating region-specific Green Factory KPIs with new data sources for site selection. Therefore, we propose a methodology involving a review of scientific literature and other sources to identify data sources for site selection, establishing research criteria for determining data suitability. The results include suitable subsets for location selection and future steps such as criteria application and target data determination. This paper contributes to paving the way for implementing sustainability-driven location selection strategies in factory planning. In conclusion, we outline a roadmap for further development and suggest two areas for future research: data collection and integration, as well as developing and validating a location selection app

Agent-based Order Release in Matrix-Structured Assembly Systems

The introduction of new variants and the difficulty of forecasting future market demand and developments aggravate the synchronisation of assembly lines. This ultimately leads to cycle time spreads and thus to efficiency losses, e.g. due to lower employee utilisation. In response, matrix-structured assembly systems have been developed as a concept of cycle time independent flow production. Essential characteristics of this type of assembly systems are the dissolution of both one-dimensionally arranged assembly stations as well as cycle times across assembly stations. In recent years, the focus has been on assembly control for the routing of orders through a matrix-structured assembly system. However, order release strategies have largely been neglected, which means that the actually promised performance of this new organisational form of assembly cannot be fulfilled. An agent-based release decision enables the optimal scheduling of new orders taking into account current information from the assembly system such as station states or the processing progress of orders that have already been released. This work extends and builds on existing agent-based approaches to control matrix-structured assembly systems in regard to order release. This results in a theoretical improvement in key performance indicators such as throughput time and station utilisation. For this purpose, the release process, as well as the associated calculation logics and constraints, are described and the implementation in an environmental model is outlined. An essential part of calculation logics is the prediction of all possible paths and capacity requirements resulting from routing and sequence flexibility. This work contributes to the practical realisation and economic operation of matrix-structured assembly systems