@inproceedings{BremerBeerTsai, author = {Bremer, Peik and Beer, Jakob E. and Tsai, Kune-muh}, title = {A Systems Theory Approach to the Performance Analysis of Robotic Compact Storage and Retrieval Systems: An Autostore Case Study}, series = {Proceedings of the 28th International Symposium on Logistics (ISL 2024) Building Sustainable Connectivity through Logistics and Supply Chains}, booktitle = {Proceedings of the 28th International Symposium on Logistics (ISL 2024) Building Sustainable Connectivity through Logistics and Supply Chains}, isbn = {978-0-85358-354-7}, pages = {177-184}, abstract = {Purpose of this paper: Robotic compact storage and retrieval systems (RCSRS) such as the AutoSto-reTM are very popular these days. A standardized yet flexible concept, plug-and-play control software and manageable investment and operating costs have made AutoStore systems a bestseller and inspired other companies to venture into developing their own RCSRS. RCSRS in general and AutoStore in particular are highly encapsulated systems in which design, dimensioning and performance analysis during operation are based to a large extent on simulation studies. However, simulation-based per-formance analysis does not cover the actual workload of the system or the specifics of the logistics environment and does not take into account the sys-tem environment, such as the WMS, the middleware that connects the Au-toStore controller to the WMS, or the UnifyAnalytics data analytics tool now provided by AutoStore. In addition, simulation studies do not provide ware-house managers with guidance on tactical decisions such as whether dividing bin locations into compartments or operational decisions (e.g. opening or clos-ing picking ports) to improve overall system performance. The purpose of this paper is to develop and test a systems theory approach to the performance of RCSRS, using an AutoStore as a case study. Design/methodology/approach: Following a systems theory approach, we define the AutoStore system as (a) the RCSRS with robots, storage bins, and picking ports (hardware), (b) the Au-toStore control software, middleware, WMS and UnifyAnalytics service (soft-ware), (c) the pickers and warehouse managers (people) and (d) the logistics and business environment. We then, in a case study, analyze an AutoStore installation in a German company in terms of its performance and correlate productivity losses with parameters of the system. We have purposefully se-lected the case company's AutoStore for its potential to generalize findings. Findings: RCSRS such as the AutoStore are heavily dependent on a steep Pareto distri-bution for good performance. Our case study shows how dividing storage bins into compartments can jeopardize the performance of an RCSRS. If a compa-ny wants to use compartments to create more storage locations in the Au-toStore, it must change its unit of analysis from SKUs to bins in the simulation studies used in the design and dimensioning phase and deploy a middleware that is able to maintain an established ABC distribution of bins in the putaway process. Our case study also shows that warehouse managers have limited options to improve the performance of the system at runtime: they can only switch picking ports on or off. We propose a dashboard fed with live data from the AutoStore to help warehouse managers make this decision. Value: This paper is a contribution to the still relatively small literature on RCSRS. It goes beyond previous studies that mainly focused on algorithmic improvement of system details. In particular, it emphasizes the impact of tactical decisions made during the design of the system on the operational performance of the system. Furthermore, it demonstrates the limited operational levers available to warehouse managers and makes a strong case for adopting a systems the-ory approach to RCSRS design. Research limitations/implications: So far, our approach has only been tested on one installation of an AutoStore system. It should be tested more thoroughly when applied to other installations and other RCSRSs. Since RCSRS performance is highly dependent on the lo-gistical and business environment, future research should aim to first classify these environments and then perform detailed analysis within each class. Practical implications: Companies operating an AutoStore can use our approach as a guide for ana-lyzing the performance of the system. Adopting a systems theory perspective in the sales phase of an RCSRS can improve design decisions and help com-mission "better" systems, i.e., systems that better fit the target company's business and logistics environment and meet the performance suggested in pre-sales simulation studies. We also offer a solution for warehouse managers to understand, from a system performance perspective, when it is advisable to turn picking ports on or off and when not.}, language = {en} } @inproceedings{ChenBremerSchmittetal., author = {Chen, Mei-Hui and Bremer, Peik and Schmitt, Jan and Tsai, Kune-muh}, title = {Reentrant Flow Shop Production Control with the Theory of Constraints for Wafer Fabrication Having Parallel Machines}, series = {Proceedings of the 28th International Symposium on Logistics (ISL 2024) Building Sustainable Connectivity through Logistics and Supply Chains}, booktitle = {Proceedings of the 28th International Symposium on Logistics (ISL 2024) Building Sustainable Connectivity through Logistics and Supply Chains}, isbn = {978-0-85358-354-7}, pages = {131-132}, abstract = {Purpose of this paper: In a production line with capacity constraint resources (CCR) or bottleneck stations, the production control and the throughput rate are determined by the CCR station. In this study, we consider a production system with parallel machines and there are many rounds of reentrants during the production processes, and can be regarded as a reentrant flow shop process (RFS). In most RFS systems, the release of jobs is a push type without considering the WIP in each layer of reentrance. To resolve the excessive WIP in an RFS system, we consider the theory of constraints (TOC) and implement the DBR (drum, bottleneck and rope) to model RFS scheduling and to define appropriate buffer sizes at the CCR stations of diverse reentrant layers. Design/methodology/approach STS: We obtain production data of a type of semiconductor chip where the photolithography process is the most frequent reentrant. We designed nine scenarios based on the current RFS of the case company by applying the TOC and considering the time differences in parallel machines. A simulation model for the photolithography process was established using AutoMod simulation. Thirty simulation runs were performed for the mean and standard deviation. The goal is to identify the best scenario among the nine proposed ones. Findings: The simulation results demonstrated that Scenario 9, which involves dynamic buffers and assigning higher priority to products with more processing reentrance layers, achieved the highest throughput of finished products. The throughput of finished products in Scenario 9 is 22\% higher than in the base scenario. It also shows improvements in maximum product stack-up and input-output ratio compared to the base scenario. Value: The paper studies dispatching rules for reentrant flow lines having parallel machines with data from the semiconductor industry, and this type of production system is common for producing a wide range of electronic devices. With limited buffer sizes on the shop floor, the number of WIPs is significant, especially for reentrant flow shops, to avoid being clogged with too many WIPs. Implementing DBR modeling from TOC, the nine scenarios demonstrate the effects of controlling buffer sizes on system performances. Research limitations/implications: The nine scenarios are designed based on the case company situations and may not be readily implemented in other industries. Moreover, the DBR modeling of the buffer sizes and CCR station schedule control should also be adjusted when employed in other applications.}, language = {en} }