Eckart Hauck

Self-optimising Production Systems

One of the central success factors for production in high-wage countries is the solution of the conflict that can be described with the term “planning efficiency”. Planning efficiency describes the relationship between the expenditure of planning and the profit generated by these expenditures. From the viewpoint of a successful business management, the challenge is to dynamically find the optimum between detailed planning and the immediate arrangement of the value stream. Planning-oriented approaches try to model the production system with as many of its characteristics and parameters as possible in order to avoid uncertainties and to allow rational decisions based on these models. The success of a planning-oriented approach depends on the transparency of business and production processes and on the quality of the applied models. Even though planning-oriented approaches are supported by a multitude of systems in industrial practice, an effective realisation is very intricate, so these models with their inherent structures tend to be matched to a current stationary condition of an enterprise. Every change within this enterprise, whether inherently structural or driven by altered input parameters, thus requires continuous updating and adjustment. This process is very cost-intensive and time-consuming; a direct transfer onto other enterprises or even other processes within the same enterprise is often impossible. This is also a result of the fact that planning usually occurs a priori and not in real-time. Therefore it is hard for completely planning-oriented systems to react to spontaneous deviations because the knowledge about those naturally only comes a posteriori.

CloudLogistic – Line-Based Optimization for the Disposition of LTL Shipments

As a real application of the in Tummel et al. (The Multi-Depot Heterogeneous Fleet Vehicle Routing Problem With Time Windows And Assignment Restrictions (m-VRPTWAR), 2011) introduced problem class m-VRPTWAR – the “multi-depot heterogeneous fleet vehicle routing problem with time windows and assignment restrictions” – this paper will introduce the so-called “CloudLogistic” concept. The problem addresses the assignment of a set of shipments to a set of freight routes in order to minimize unused cargo volume of the vehicles. The assignment of each shipment is restricted to a subset of freight routes. Furthermore, the shipment has to be delivered in a specific time window. Therefore, it is necessary to determine an order of shipments for each freight route that guarantees the observance of all time windows. The problem class m-VRPTWAR abstracts the implied optimization problem. Besides the introduction of the “CloudLogistic” concept, the main requirements for the software-based shipment processing are discussed, which is the central part of a software-based solution for an implied freight cooperation of Less Than Truckload (LTL) shipments. For the evaluation of problem-specific solvers, as well as for an improved evaluation of the feasibility of the m-VRPTWAR, realistic test data come into place according to Tummel et al. (An Incremental Online Heuristic for Evaluating the Feasibility of the m-VRPTWAR, 2011). Besides a detailed description of the concept a method for the generation of realistic test data will be presented. Finally the evaluation of a Repacking First Fit approach (RFF) as a solution for the discussed feasibility check will be extended by considering different choices of repacking depths.

The Multi-Depot Heterogeneous Fleet Vehicle Routing Problem With Time Windows And Assignment Restrictions (M-VRPTWAR)

In this paper, the multi-depot heterogeneous fleet vehicle routing problem with time windows and assignment restrictions (m-VRPTWAR) is introduced. The problem addresses the assignment of a set of shipments to a set of freight routes so that unused cargo volume of the vehicles is minimized. The assignment of each shipment is restricted to a subset of the freight routes. Furthermore, the shipment has to be delivered in a specific time window. Thus, it is necessary to determine an order of the shipments of each freight route that guarantees the observance of all time windows. Firstly, a formulation of an integer linear program (ILP) for solving the m-VRPTWAR is developed and the problem is proven to be NP-hard. Afterwards, the ILP is evaluated by solving several large-scale scenarios using the solvers CPLEX and Gurobi.

An Incremental Online Heuristic For Evaluating The Feasibility Of The M-VRPTWAR

In this paper, a heuristic approach for evaluating the feasibility of an instance of the Multi-Depot Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Assignment Restrictions (m-VRPTWAR) is presented. The heuristic approach tries to find a feasible solution by solving two sub-problems of the m-VRPTWAR: a 3-Dimensional Variable-sized Bin-Packing problem (3DVSBPP) and a Traveling Salesman Problem with Time Windows (TSPTW). In order to address the first problem, an online algorithm is presented. This algorithm expects shipments to be inserted in an online fashion and assigns them to freight routes by first-fit. Repacking already assigned shipments is permitted. The TSPTW part of the problem is addressed by a 2-phase heuristic that is based on algorithms presented in Savelsbergh (1985) and Ascheuer (1996). If there is no feasible solution for a new shipment, this shipment will be rejected. The heuristic approach is evaluated by solving several large-scale scenarios and monitoring the rejection rate of the algorithm.

Serendipity rendezvous as a mitigation of exploration's interruptibility for a team of robots

Dependence on a team of robots to carry out the exploration missions has many benefits such as speeding up the missions; provided that the coordination among robots is maintained. Many circumstances can limit the communication, which is crucial for the coordination among robots (e.g. impenetrable barriers, high temperature etc.). A periodic rendezvous strategy is considered in this paper as a work around in order to overlap communication ranges of the robots. Attending these periodic rendezvous sessions requires that the robots interrupt their current exploration progress periodically and traverse back to the rendezvous points (i.e. Interruptibility). During their trips to these points, they do not gain new knowledge since they cross already explored parts of the area. Therefore, using rendezvous strategies improves the team behavior but has a negative impact on the time efficiency. The contribution of this paper is to mitigate this negative impact of Interruptibility on explorations while maintaining the coordination among robots. The mitigation algorithm is evaluated on several graphs and its performance is compared with other rendezvous approaches where the results are promising.

Trust Is Good, Control Is Better - An Open Innovation-Controlling for SME

Until now the practical work concerning Open Innovation was focused on the conceptual and use-oriented field. Both the methods and their potentials are depicted but there is no research on the cost-effectiveness of Open Innovation and the applicability of its methods – especially in Small and Medium Enterprises (SME). Currently SME have no instrument helping them to decide whether they should adopt Open Innovation. Hence it is necessary to create such an instrument to give the SME support to decide if “the formal discipline and practice of leveraging the discoveries of others as input for the innovation process through formal and informal relationships” [RP08] is worthwhile. In this paper the research project “Invoice – Efficiency of Open Innovation for Small and Medium-sized Enterprises” is presented. Within this project the Institute for Management Cybernetics e.V. (IfU) and the Technology and Innovation Management Group (TIM) at RWTH Aachen University develop an instrument to control Open Innovation-methods in SME.

Design and implementation of a vehicle dynamics control system by means of torque vectoring for an autonomous vehicle

This paper describes to which extent the operational envelope of scaled vehicles can be extended by integrating a vehicle dynamics control system using torque vectoring. A detailed description for the construction of a mechatronic basis for an autonomous model car in a 1:10th scale is given. The design of the vehicle only uses standardized components and allows the most possible flexibility of controlling the vehicles dynamics behavior by applying individual driving moments to the wheels.

CloudLogistic – Geschäftsmodellentwicklung für eine Frachtenkooperation kleiner und mittlerer Straßengüterverkehrsunternehmen im Teilladungssegment

Dieser Beitrag adressiert einen ersten Entwurf eines Geschaftsmodells fur eine Frachtenkooperation von kleinen und mittleren Speditionsunternehmen des Strasenguterverkehrs im Bereich von Teilladungstransporten. Zunachst erfolgt eine kurze Einfuhrung, in der die Relevanz von Frachtenkooperationsbildungen kleiner und mittlerer Speditionsunternehmen aufgezeigt wird. Im Gegensatz zum Stuckgut- und Komplettladungsbereich existiert fur den Transport von Teilladungen allerdings bis dato noch kein optimiertes Logistikkonzept fur klein- und mittelstandische Transportnetzwerke im Strasenguterverkehr. Das CloudLogistic-Szenario wird als ein geeigneter Ansatz vorgestellt, um dieser Problemstellung zu begegnen. Den Kern dieses Beitrags bildet der Geschaftsmodellentwurf fur diesen Frachtenkooperationstyp mittels der Business-Model-Canvas-Methodik von Osterwalder/Pigneur, da dieser Ansatz gerade fur die Eingangsphase im Rahmen von Geschaftsmodellkonzeptionen bzw. bei Geschaftsmodellinnovationen geeignet ist. Der Beitrag empfiehlt, den Entwurf des Geschaftsmodells um eine geeignete Business-Architektur, die die relevanten Geschaftsprozesse im Hinblick auf die sich anschliesende Konzipierung der IT-Architektur fur die optimierte Zentraldisposition beinhaltet, zu erweitern.

Line-based optimization of LTL-shipments using a multi-step genetic algorithm

Motivated by the so-called “Cloud Logistic”-concept as an innovative, line-based way for dealing with less than truck load (LTL) shipments in cooperation networks, this paper introduces a genetic algorithm as a heuristical approach for dealing with multi-objective optimization problems. Based on the implied optimization problem - the NP-hard multi-depot heterogeneous fleet vehicle routing problem with time windows and assignment restrictions (m-VRPTWAR) - four different optimization goals of the “CloudLogistic”-concept are introduced and a multi-step approach is motivated. Therefore, two different optimization steps are presented and transferred into a genetic algorithm. Additionally, two innovative problem-specific genetic operators are introduced by combining a generation-based approach and a usage-based approach in order to create a useful mutation process. A further usage-based approach is used to realize a problem-specific crossover operator. The presented genetic multi-step approach is a useful concept for dealing with multi-objective optimization problems without the need of a single combined fitness function.

Key Performance Indicators for the Impact of Cognitive Assembly Planning on Ramp-up Process

Within the ramp-up phase of highly automated assembly systems, the planning effort forms a large part of production costs. Due to shortening product lifecycles, changing customer demands and therefore an increasing number of ramp-up processes these costs even rise. So assembly systems should reduce these efforts and simultaneously be flexible for quick adaption to changes in products and their variants. A cognitive interaction system in the field of assembly planning systems is developed within the Cluster of Excellence “Integrative production technology for high-wage countries” at RWTH Aachen University which integrates several cognitive capabilities according to human cognition. This approach combines the advantages of automation with the flexibility of humans. In this paper the main principles of the system’s core component – the cognitive control unit – are presented to underline its advantages with respect to traditional assembly systems. Based on this, the actual innovation of this paper is the development of key performance indicators. These refer to the ramp-up process as a main objective of such a system is to minimize the planning effort during ramp-up. The KPIs are also designed to show the impact on the main idea of the Cluster of Excellence in resolving the so-called Polylemma of Production.