@book{Bremer, author = {Bremer, Peik}, title = {Integriertes F{\"u}hrungskonzept f{\"u}r Projekte des Anlagenbaus}, publisher = {Shaker}, address = {Aachen}, language = {de} } @inproceedings{BremerHsuTsaietal., author = {Bremer, Peik and Hsu, Yuan-Chin and Tsai, Kune-muh and Huang, Echo}, title = {Measuring Supply Chain Adaptability: A Case Study in Solar PV Industry}, series = {Proceedings of the 20th International Symposium on Logistics "Reflections on Supply Chain Research and Practice" (ISL 2015), Bologna, Italy}, booktitle = {Proceedings of the 20th International Symposium on Logistics "Reflections on Supply Chain Research and Practice" (ISL 2015), Bologna, Italy}, pages = {502 -- 508}, abstract = {While the world is struggling with shortage of fossil fuels energy and seeking for alternatives to it over the past several years, experts and investors have already identified renewable energy as alternative energies for fossil fuels and nuclear power. Among different types of energies, solar energy is considered as one of the most environmental friendly source. Not to mention that investment in solar photovoltaic (PV) industry had become a boom especially after the 21st century. However, due to the volatile of demand and changing patterns in manufacturing and distribution between several countries, the industry started to collapse. For this reason, many of PV related companies eventually have gone bankruptcy. Several methods, such as efficiency, responsiveness and agility, which are used to measure competitive factors for a company, have already been widely applied. Nevertheless adaptability is still a new and largely unexplored area. As a result, our research aims to develop a mechanism to measure supply chain adaptability under radical environment by building up case studies and extracting potential elements for metrics of solar PV industry. Qualitative research is conducted as our methodology, which combined with company reports, industry statistics, literature review and six semi-structured interviews with solar energy related companies in Germany. In our case studies, six companies specialize in different aspects of solar PV supply chain and demonstrate different emphasis regarding the adaptability of supply chain. Based on our result, company could assess their individual contributions and evaluate what abilities they are insufficient for preventing the risks involved when encountering volatile changes in the market.}, language = {en} } @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{BremerHarishSainietal., author = {Bremer, Peik and Harish, Shreelekha and Saini, Sweta and Weberbauer, Frauke}, title = {The Distribution Logistics of Covid-19 Vaccines in Germany: A Case Study}, series = {29th International Symposium on Logistics "Embedding Circularity in Supply Chains", Wiesbaden, 6.-9. Juli 2025}, booktitle = {29th International Symposium on Logistics "Embedding Circularity in Supply Chains", Wiesbaden, 6.-9. Juli 2025}, editor = {Potter, Andrew and Pawar, Kulwant S. and Kalverkamp, Matthias and Rogers, Helen}, isbn = {978-0-85358-354-7}, pages = {392-403}, abstract = {Purpose of this paper: The global rollout of COVID-19 vaccines has been one of the most significant public health measures in modern history. The logistics systems of the vaccination campaigns were key to both their effectiveness and efficiency. This paper examines the logistical framework conditions of the German COVID-19 vaccination campaign and analyses vaccine distribution in ultra-cold supply chains in order to contribute to a better understanding of the design of challenging logistics systems in the field of tension between public and private actors. Design/methodology/approach: We use a case study approach to look at the COVID-19 vaccination campaign in Germany where the federal structure gives the 16 federal states (the units of analysis in the case study) a decision-making authority in health-related issues that was also reflected in the various logistics systems that were implemented for the campaign. Primary data was obtained through in-depth interviews and enriched with secondary data from newspapers and other sources. The cases were analysed through the theory lens of the collaborative governance framework. Findings: Federalism leads to braking effects where a rapid, coordinated and technically excellent response would be required. Although the vaccination campaign was an overall success, some logistical processes lacked GDP (Good Distribution Practice) approval, so the start was a bit bumpy. The opportunity to develop standard procedures for similar situations in the future was not properly utilised, reducing preparedness to a level below what was possible. Value: This case study is one of the few empirical works that deal with the logistical systems and processes behind vaccination campaigns. In particular, it sheds light on the interplay between public and private actors in a federal government structure. Research limitations/implications: Primary data could only be obtained from four of the 16 federal states. This is mainly due to the fact that dealing with the COVID-19 pandemic in Germany is still an open issue and an unparalleled political minefield. Practical implications: The research shows that standardised, GDP-approved and configurable logistics processes together with a strategic inventory of equipment, infrastructure and consumables are key elements to be prepared for similar situations in the future.}, 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} } @inproceedings{GuoBremerLirnetal., author = {Guo, J.-J. and Bremer, Peik and Lirn, Taih-Cherng and Chen, S.}, title = {A study on the acceptance of autonomous container trucks in Taiwan}, series = {The 20th Asia Maritime \& Fisheries University Forum 2022, Mokpo, South Korea}, booktitle = {The 20th Asia Maritime \& Fisheries University Forum 2022, Mokpo, South Korea}, language = {en} } @inproceedings{MeyerPechtlBremeretal., author = {Meyer, Maximilian and Pechtl, Lin and Bremer, Peik and Schmitt, Jan}, title = {Towards position-based technologies for digitized process management on the shop floor}, series = {Proceedings of the 24th International Symposium on Logistics - Supply Chain Networks vs Platforms: Innovations, Challenges and Opportunities, W{\"u}rzburg}, booktitle = {Proceedings of the 24th International Symposium on Logistics - Supply Chain Networks vs Platforms: Innovations, Challenges and Opportunities, W{\"u}rzburg}, pages = {232 -- 241}, abstract = {Position-based technologies, e.g Ultrawideband (UWB), WiFi or Bluetooth, for indoor localisation purposes are already commercially available. With the highly increasing digitalization of industrial processes, the potential of these technologies comes into focus of process management research. This paper aims to structure position-based technologies according to their potential to support shop-floor process management. For this purpose, a framework with the following dimensions is developed: technical performance properties of the IPS, economical aspects, relevant use-case requirements, and appropriate data aggregation strategies. Following this, two representable use-cases show the implementation of an indoor-positioning-system and the data aggregation in order to derive relevant process data from position data.}, language = {en} } @inproceedings{BremerAlyonesHenzetal., author = {Bremer, Peik and Alyones, Hani and Henz, Yannic and Hoch, Anna-Lena and Mauer, Manuel and Nassar, Abdelrahman and Tafel, Matthias}, title = {Non-immersive NFC-based Smart Wearable for Picker-to-Parts Order Picking}, series = {Proceedings of the 26th International Symposium on Logistics - The Journey to Sustainable Supply Chains, Cork, Ireland}, booktitle = {Proceedings of the 26th International Symposium on Logistics - The Journey to Sustainable Supply Chains, Cork, Ireland}, pages = {44 -- 44}, abstract = {Purpose of this paper: Surveys have shown that most companies still use paper-based lists or RF handhelds to support picker-to-parts order picking. More modern approaches like Pick-by-Voice or Pick-by-Vision are gaining ground but have raised concerns about cognitive ergonomics. More recently, smart wearables for order picking with integrated or wirelessly connected barcode scanners have arrived on the market. The purpose of this paper is to discuss details of a smart wearable that uses Near-Field Communication (NFC) which allows confirming storage bins and order bins without any input from the order picker. Design/methodology/approach: Starting from a Business Process Model and Notation (BPMN) concept of the order picking process and informed by both an analysis of existing smart wearables and a literature review of design guidelines for user interfaces on smart wearables, a smart wearable was designed from scratch. The technical design, which focuses on order pickers' productivity, features (1) a novel approach to using NFC for order picking support, (2) a streamlined user interface, and (3) a fast middleware connecting the smart wearable to a Warehouse Management System (WMS). Findings: Industrial smartwatches often come with an NFC reader integrated into the display, requiring non-ergonomic movements of arm and hand when reading NFC tags on storage bins. Antenna extenders directly connected to the integrated NFC reader can be placed arbitrarily in more ergonomic positions (e.g., in a glove) but at the cost of reducing the reading distance substantially. An additional, separate active NFC reader, however, can smoothly identify storage bins while moving the hand at the usual arm operation speed of 2 m/s and retains the option of using antenna extenders. Careful design of the user interface is key to smooth and fast picking; the small screen size is a neglectable restriction. Value: This paper contributes to the still relatively small body of literature on smart wearables in order picking by discussing design features in detail - technical ones (such as the integration of an NFC reader) as well as the user interface. Research limitations/implications: The NFC-based smart wearable is a prototype and has not been tested in industrial applications yet. Practical implications: This paper increases the technical options available for supporting picker-to-parts order picking.}, language = {en} } @article{PerottiBastidasSantacruzBremeretal., author = {Perotti, Sara and Bastidas Santacruz, Roman Felipe and Bremer, Peik and Beer, Jakob Emanuel}, title = {Logistics 4.0 in warehousing: a conceptual framework of influencing factors, benefits and barriers}, series = {The International Journal of Logistics Management}, volume = {33}, journal = {The International Journal of Logistics Management}, number = {5}, publisher = {Emerald Publishing Limited}, issn = {0957-4093}, doi = {10.1108/IJLM-02-2022-0068}, pages = {193 -- 220}, abstract = {Purpose: In the last decade, the Industry 4.0 paradigm had started to rapidly expand to the logistics domain. However, Logistics 4.0 is still in an early adoption stage: some areas such as warehousing are still exploring its applicability, and the technological implementation of this paradigm can become fuzzy. This paper addresses this gap by examining the relationship among influencing factors, barriers, and benefits of Logistics 4.0 technologies in warehousing contexts. Design/methodology/approach: Starting from a Systematic Literature Review (SLR) approach with 56 examined documents published in scientific journals or conference proceedings, a conceptual framework for Logistics 4.0 in warehousing is proposed. The framework encompasses multiple aspects related to the potential adopter's decision-making process. Findings: Influencing factors toward adoption, achievable benefits, and possible hurdles or criticalities have been extensively analyzed and structured into a consistent picture. Company's digital awareness and readiness result in a major influencing factor, whereas barriers and criticalities are mostly technological, safety and security, and economic in nature. Warehousing process optimization is the key benefit identified. Originality/value: This paper addresses a major gap since most of the research has focused on specific facets, or adopted the technology providers' perspective, whereas little has been explored in warehousing from the adopters' view. The main novelty and value lie in providing both academics and practitioners with a thorough view of multiple facets to be considered when approaching Logistics 4.0 in logistics facilities.}, language = {en} } @inproceedings{BremerChenChenetal., author = {Bremer, Peik and Chen, Mei-hui and Chen, Jung-hung and Tsai, Kune-muh}, title = {A Case Study on De-Risking Plans for Stronger Supply Chain Resilience}, series = {Proceedings of the 19th International Symposium on Logistics "Designing Responsible and Innovative Global Supply Chains" (ISL 2014), Ho Chi Minh City (Vietnam)}, booktitle = {Proceedings of the 19th International Symposium on Logistics "Designing Responsible and Innovative Global Supply Chains" (ISL 2014), Ho Chi Minh City (Vietnam)}, pages = {80 -- 85}, abstract = {Recent risk incidents, such as 911 attacks, financial crisis, catastrophic disasters like earthquakes and floods, etc. have added challenges and susceptibility for business operations. In encountering more frequent and unpredictable risks than before, many companies adopt risk management systems and redesign their supply chain (SC) structures for stronger SC resilience as well as quicker recovery speed. In this paper, we present a case study of a large semiconductor packaging and testing company in Taiwan, AKH, in confronting risk incidents and the plans they implemented to strengthen the SC resilience to assure more reliable supply of their products and services to the customers worldwide. AKH executed several de-risking plans, which can be divided into four Rs - resourcefulness, redundancy, robustness and rapidity. Many of the de-risking plans rely on the E-Hub system the company implemented a few years ago for SC information visibility. After carrying out the de-risking plans, AKH found that the suppliers and customers as well as the company have to furnish additional kinds of information to the E-Hub system in order to improve the SC resilience and assess the impacts of risk incidents. The results show improved SC resilience for the case company in encountering risk incidents and much faster recovery speed once an incident occu}, language = {en} } @inproceedings{ChenBremerGuoetal., author = {Chen, Mei-Hui and Bremer, Peik and Guo, Shin-Ming and Lin, Po-Jen and Tsai, Kune-muh}, title = {Material stacking problem detection with Mask R-CNN for Storage safety}, publisher = {International Symposium on Logistics "Managing Supply Chains during Geopolitical Turbulence", Enschede, 9.-12- Juli}, pages = {6}, abstract = {Purpose of this paper: Image processing technology has gained much improvement in recent years. In smart warehousing, most focus is on warehouse operations to improve efficiency and save human labors. However, in put-away, re-warehousing or picking process, after being handled by forklifts or laborers, the stacking of inventory items may change its shape and balance due to deviation, compression, tilting, etc., which may jeopardize the safety of stored goods and even people working in the warehouse. If there is a system that could monitor the stacking of inventory items all the time and could alarm managers should the stacking tilts or deforms to a certain level, inventory safety could be vastly improved. This study is on smart warehouse safety problems emphasizing at goods stacking to avoid the possibility of falling or collapse through image processing via Mask R-CNN. Our experiment is limited to items that form a rectangular block on a pallet, such as wooden bars, cartons or any box-shaped items. Design/methodology/approach STS: Mask R-CNN is a deep learning software and can be used in a wide range of applications. In this study, we used Mask R-CNN to detect the images of stacked items to see if the stacking is stable. We took photos from a warehouse and divided them into three classes - training, validation and production. VGG Image Annotator (VIA) was used for object annotation. To detect the tilt degree of stacked items, we derived formulation from book- stacking problems and retrieved dot coordinates of square frames encompassing objects in an image from the result of Mask R-CNN for calculation. Findings: Because there is a limited number of photos for training, validation and production, we applied image enhancement techniques such as flipping, affinity, multiplication, etc. to increase the total number of images to avoid over-fitting during the training process. The trained Mask R-CNN network demonstrated its capability in framing objects and after retrieving the dot coordinates of the frames, it could compute the degree of tilt as a reference for block stacking alarm. Value: The paper presents a relatively rare study of applying deep learning techniques on images as applied to material stacking safety problems. It contributes to a special smart warehousing domain. The same technique can be applied to inventory counting and help improve labor-saving in counting and in locating items in a warehouse. Research limitations/implications: Due to the limited number of images and restricted angles of taking the images, Mask R- CNN may not be so capable in framing objects of special angles of images. More images with diverse angles of them should be obtained for training to improve the capability of the trained network. Practical implications: Successful implementation of the technology developed in this study in a warehouse monitoring system can help industries in smart detection of improper stacking to assist human in improving the accuracy of safety judgement and can also save labors in reviewing images or records of a warehouse.}, language = {en} }