Felix Böse

Catalogue of Criteria for Autonomous Control in Logistics

Over the past years an increase in complexity of production and logistics systems regarding organisational, time-related and systemic aspects could be observed (Philipp et al. 2006). As a result, it is often impossible to make all necessary information available to a central entity in real time and to perform appropriate measures of control in terms of a defined target system. This development is caused by diverse changes, for example, short product life cycles as well as a decreasing number of lots with a simultaneously rising number of product variants and higher product complexity (Scherer 1998). Hence, new demands were placed on competitive companies, which cannot be fulfilled with conventional control methods. Conventional production systems are characterized by central planning and control processes, which do not allow fast and flexible adaptation to changing environmental influences. Establishing autonomous control seems to be an appropriate method to meet these requirements. The major aim of establishing autonomous logistics processes is to improve the logistics system’s performance. The basis for achievement of this objective is a comprehensive understanding of the term autonomy in the context of logistics processes. The idea of autonomous control is to develop decentralised and heterarchical planning and controlling methods in contrast to existing central and hierarchical planning and controlling approaches (Scholz-Reiter et al. 2006).

Autonomously controlled storage management in vehicle logistics – applications of RFID and mobile computing systems

Today, planning and control of logistic processes on automobile terminals are generally executed by centralised logistics systems, which cannot cope with high requirements for flexible order processing due to increasing dynamics and complexity. The main business processes on automobile terminals – notification of vehicles by automobile manufacturer, transport to automobile terminal, storage and technical treatment as well as delivery to automobile dealer – are planned and controlled by centralised application software systems. In the context of this article, an innovative approach to autonomous control in automobile logistics is investigated, considering as example the logistic order processing of an idealised automobile terminal of the company E.H. Harms Automobile‐Logistics. Within a simulation study, evidence of the existing application potential of autonomous control in the field of vehicle storage management is provided. Thereupon the technical feasibility of an autonomously controlled storage manage...

Complexity cube for the characterization of complex production systems

Owing to the increasing complexity of todays logistic systems, new planning and control methods are necessary. Autonomously controlled processes are a possible solution to cope with these new requirements. In order to verify this thesis, the development of an evaluation system is necessary which measures the logistic objective achievement, the level of autonomous control and the level of complexity. The current paper presents adequate operationalization of the complexity in production systems. For this purpose a complexity cube is derived in order to characterize production systems regarding their level of complexity. The different types of complexity in this cube are represented by vectors which allow measurement and comparison of different types of complexity for different production systems. The application of the complexity cube is illustrated using an exemplary job shop manufacturing scenario.

Application of a three-component evaluation system for autonomous control in logistics

Abstract Autonomous control of logistic systems is a potential solution to the problems encountered in modern competitor marketplaces. Autonomous control in a logistic system is characterized by the ability of logistic objects (e.g. order, pallet, machine) to process information in order to render and execute decisions on their own. In order to determine the limitations of autonomy an evaluation system is needed which is presented in this paper. The evaluation system is created by three components which can be combined to analyse the potential of autonomous control. This potential is visualized by the result of the evaluation procedure with the help of a three-dimensional (3D) diagram built from single curves. Simulation studies are used to verify the surface of the 3D diagram and highlight the limitations of the autonomous control approach. All the varied parameters (level of autonomous control, level of complexity, and level of logistic objective achievement) are described and measured in the simulation study.

Autonomously Controlled Storage Allocation on an Automobile Terminal

Today, planning and control of logistic processes on automobile terminals are generally executed by centralised logistics systems, which in many cases cannot cope with the high requirements for flexible order processing due to increasing dynamics and complexity. The main business processes on automobile terminals — notification of vehicles by automobile manufacturer, transport to automobile terminal, storage and technical treatment as well as delivery to automobile dealer — are planned and controlled by a central application software system. By establishing autonomous control, vehicles are enabled to render decisions on their own and according to this determine their way through a logistics network on the basis of an own system of objectives.

Business Process Modelling of Autonomously Controlled Production Systems

Conventional production systems are characterised by central planning and control methods, which show a wide range of weaknesses regarding flexibility and adaptability of the production system to environmental influences. Centralised planning and control methods are based on simplified premises (predictable throughput times, fix processing times of production orders etc.), which lead to an inadequate and unrealistic description of the production system. The different centralised planning steps of the traditional ERP respectively MRP based PPC-Systems are executed sequentially, therefore adaptation to changing boundary conditions (e.g. planning data) is only possible within long time intervals. This means that changes to the job shop situation cannot be considered immediately, but during next planning run at the earliest. As a result, current planning is based on old data and the needed adaptation measures cannot be performed in time for a proper reaction of the discrepancy between the planned and the current situation (Scholz-Reiter et al. 2006). In case of disturbances or fluctuating demands, centralised planning and control methods are insufficient to deal with the complexity of the comprehensive planning tasks of centralised systems, which rises disproportionately to their size and heavily constrains fault tolerance and flexibility of the overall system (Kim and Duffie 2004; Prabhu and Duffie 1995).

Der Komplexitätswürfel: Ein Instrumentarium zur Charakterisierung komplexer Produktionssysteme

Kurzfassung Die Selbststeuerung logistischer Prozesse stellt einen innovativen Ansatz zum flexiblen und adaptiven Umgang mit der zunehmenden Komplexität heutiger Logistiksysteme dar. Zur Validierung dieser Aussage ist ein Evaluierungssystem notwendig, das eine Bestimmung des logistischen Zielerreichungsgrads in Abhängigkeit vom Selbststeuerungsgrad und der Komplexität eines Produktionssystems erlaubt. Im Rahmen dieses Beitrags wird dafür ein Komplexitätswürfel vorgestellt, welcher die Produktionssysteme hinsichtlich verschiedener Komplexitätskategorien durch Vektoren charakterisiert.