ORCID Profile
0000-0001-5109-9627
Current Organisation
Technische Universität Braunschweig Fakultät für Maschinenbau
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Publisher: Springer International Publishing
Date: 2018
Publisher: Elsevier BV
Date: 2012
Publisher: IEEE
Date: 12-2017
Publisher: IEEE
Date: 2005
Publisher: IGI Global
Date: 2020
DOI: 10.4018/978-1-5225-9019-4.CH007
Abstract: Routing uses a unique identifier of each participating node in the network to forward the information between two nodes. Traditionally, routing takes place at the network layer of a standard network layering architecture where it takes into account the local or the global network information, albeit, the local information uses a local-scope unique identifier. One of the prime objectives of any routing strategy at the network layer is to forward data from one end to another however, the same objective can also be achieved at the data link layer by using the hardware address of each node as a unique identifier. This chapter discusses the key questions. (i.e., Why traditional routing is called IP-based routing? What if we reorient the traditional concept of routing on the data link layer? What are the positive and negative impact, to carry out routing at IP—or data link—layer?) This study may be helpful for researchers to understand the concept of IP-based routing and path selection at link layer regardless of the standard layering architecture and the type of IP address.
Publisher: Elsevier BV
Date: 07-2017
Publisher: IEEE
Date: 12-2012
Publisher: Elsevier BV
Date: 10-2018
Publisher: Informa UK Limited
Date: 16-04-2021
Publisher: Springer International Publishing
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 22-07-2016
Publisher: MDPI AG
Date: 07-03-2019
DOI: 10.3390/S19051150
Abstract: Natural disasters and catastrophes not only cost the loss of human lives, but adversely affect the progress toward sustainable development of the country. As soon as disaster strikes, the first and foremost challenge for the concerned authorities is to make an expeditious response. Consequently, they need to be highly-organized, properly-trained, and sufficiently-equipped to effectively respond and limit the destructive effects of a disaster. In such circumstances, communication plays a vital role, whereby the consequences of tasks assigned to the workers for rescue and relief services may be streamlined by relaying necessary information among themselves. Moreover, most of the infrastructure is either severely damaged or completely destroyed in post-disaster scenarios therefore, a Vehicular Ad Hoc Network (VANET) is used to carry out the rescue operation, as it does not require any pre-existing infrastructure. In this context, the current work proposes and validates an effective way to relay the crucial information through the development of an application and the deployment of an experimental TestBed in a vehicular environment. The TestBed may able to provide a way to design and validate the algorithms. It provides a number of vehicles with onboard units embedded with a credit-card-size microcomputer called Raspberry Pi and a Global Positioning System (GPS) module. Additionally, it dispatches one of the pre-defined codes of emergency messages based on the level of urgency through multiple hops to a central control room. Depending on the message code received from a client, the server takes appropriate action. Furthermore, the solution also provides a graphical interface that is easy to interpret and to understand at the control room to visualize the rescue operation on the fly.
Publisher: IEEE
Date: 12-2017
Publisher: IOP Publishing
Date: 19-11-2015
Publisher: Springer International Publishing
Date: 15-09-2016
Publisher: Springer Science and Business Media LLC
Date: 09-2021
DOI: 10.1007/S43069-021-00087-8
Abstract: The distribution/allocation problem is known as one of the most comprehensive strategic decision. In real-world cases, it is impossible to solve a distribution/allocation problem in traditional ways with acceptable time. Hence researchers develop efficient non-traditional techniques for the large-term operation of the whole supply chain. These techniques provide near optimal solutions particularly for large-scale test problems. This paper presents an integrated supply chain model which is flexible in the delivery path. As the solution methodology, we apply a memetic algorithm with a neighborhood search mechanism and novelty in population presentation method called “extended random path direct encoding method.” To illustrate the performance of the proposed memetic algorithm, LINGO optimization software serves as comparison basis for small size problems. In large-size cases that we are dealing with in real world, a classical genetic algorithm as the second metaheuristic algorithm is considered to compare the results and show the efficiency of the memetic algorithm.
Publisher: Elsevier BV
Date: 2015
Publisher: Springer International Publishing
Date: 2020
Publisher: Springer Singapore
Date: 2017
Publisher: Elsevier BV
Date: 09-2010
Publisher: Springer Science and Business Media LLC
Date: 28-01-0001
DOI: 10.1007/S40305-021-00380-7
Abstract: The distribution–allocation problem is known as one of the most comprehensive strategic decisions. In real-world cases, it is impossible to solve a distribution–allocation problem completely in acceptable time. This forces the researchers to develop efficient heuristic techniques for the large-term operation of the whole supply chain. These techniques provide near optimal solution and are comparably fast particularly for large-scale test problems. This paper presents an integrated supply chain model which is flexible in the delivery path. As solution methodology, we apply a memetic algorithm with a novelty in population presentation. To identify the optimum operating condition of the proposed memetic algorithm, Taguchi method is adopted. In this study, four factors, namely population size, crossover rate, local search iteration and number of iteration, are considered. Determining the best level of the considered parameters is the outlook of this research.
Publisher: Elsevier BV
Date: 2019
Publisher: Springer International Publishing
Date: 20-08-2017
Publisher: MDPI AG
Date: 02-02-2023
DOI: 10.3390/APP13031957
Abstract: Exponentially growing technologies such as intelligent robots in the context of Industry 4.0 are radically changing traditional manufacturing to intelligent manufacturing with increased productivity and flexibility. Workspaces are being transformed into fully shared spaces for performing tasks during human–robot collaboration (HRC), increasing the possibility of accidents as compared to the fully restricted and partially shared workspaces. The next technological epoch of Industry 5.0 has a heavy focus on human well-being, with humans and robots operating in synergy. However, the reluctance to adopt heavy-payload-capacity robots due to safety concerns is a major hurdle. Therefore, the importance of analyzing the level of injury after impact can never be neglected for the safety of workers and for designing a collaborative environment. In this study, quasi-static and dynamic analyses of accidental scenarios during HRC are performed for medium- and low-payload-capacity robots according to the conditions given in ISO TS 15066 to assess the threshold level of injury and pain, and is subsequently extended for high speeds and heavy payloads for collaborative robots. For this purpose, accidental scenarios are simulated in ANSYS using a 3D finite element model of an adult human index finger and hand, composed of cortical bone and soft tissue. Stresses and strains in the bone and tissue, and contact forces and energy transfer during impact are studied, and contact speed limit values are estimated. It is observed that heavy-payload-capacity robots must be restricted to 80% of the speed limit of low-payload-capacity robots. Biomechanical modeling of accident scenarios offers insights and, therefore, gives confidence in the adoption of heavy-payload robots in factories of the future. The analysis allows for prediction and assessment of different hypothetical accidental scenarios in HRC involving high speeds and heavy-payload-capacity robots.
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: IEEE
Date: 12-2017
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: IEEE
Date: 2016
Publisher: Elsevier BV
Date: 12-2020
Publisher: Springer London
Date: 2011
Publisher: Springer London
Date: 2011
Publisher: Springer London
Date: 2011
Publisher: Hindawi Limited
Date: 2018
DOI: 10.1155/2018/9848104
Abstract: The dynamic and stochastic vehicle routing problem (DSVRP) can be modelled as a stochastic program (SP). In a two-stage SP with recourse model, the first stage minimizes the a priori routing plan cost and the second stage minimizes the cost of corrective actions, performed to deal with changes in the inputs. To deal with the problem, approaches based either on stochastic modelling or on s ling can be applied. S ling-based methods incorporate stochastic knowledge by generating scenarios set on realizations drawn from distributions. In this paper we proposed a robust solution approach for the capacitated DSVRP based on s ling strategies. We formulated the problem as a two-stage stochastic program model with recourse. In the first stage the a priori routing plan cost is minimized, whereas in the second stage the average of higher moments for the recourse cost calculated via a set of scenarios is minimized. The idea is to include higher moments in the second stage aiming to compute a robust a priori routing plan that minimizes transportation costs while permitting small changes in the demands without changing solution structure. Additionally, the approach allows managers to choose between optimality and robustness, that is, transportation costs and reconfiguration. The computational results on a generic dynamic benchmark dataset show that the robust routing plan can cover unmet demand while incurring little extra costs as compared to the preplanning. We observed that the plan of routes is more robust that is, not only the expected real cost, but also the increment within the planned cost is lower.
Publisher: Springer London
Date: 2011
Publisher: Springer London
Date: 2011
Publisher: Springer London
Date: 2011
Publisher: Elsevier BV
Date: 2015
Publisher: Springer London
Date: 2011
Publisher: Springer London
Date: 2011
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: Elsevier BV
Date: 2011
Publisher: Elsevier BV
Date: 08-2017
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: Springer International Publishing
Date: 07-10-2018
Publisher: Informa UK Limited
Date: 06-01-2021
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: IEEE
Date: 07-2017
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: Springer International Publishing
Date: 11-11-2201
Publisher: Springer International Publishing
Date: 11-11-5000
Publisher: MDPI AG
Date: 31-05-2019
DOI: 10.3390/APP9112249
Abstract: With the development of industrial manufacture in the context of Industry 4.0, various advanced technologies have been designed, such as reconfigurable machine tools (RMT). However, the potential of the latter still needs to be developed. In this paper, the integration of RMTs was investigated in the capacity adjustment of job shop manufacturing systems, which offer high flexibility to produce a variety of products with small lot sizes. In order to assist manufacturers in dealing with demand fluctuations and ensure the work-in-process (WIP) of each workstation is on a predefined level, an operator-based robust right coprime factorization (RRCF) approach is proposed to improve the capacity adjustment process. Moreover, numerical simulation results of a four-workstation three-product job shop system are presented, where the classical proportional–integral–derivative (PID) control method is considered as a benchmark to evaluate the effectiveness of RRCF in the simulation. The simulation results present the practical stability and robustness of these two control systems for various reconfiguration and transportation delays and disturbances. This indicates that the proposed capacity control approach by integrating RMTs with RRCF is effective in dealing with bottlenecks and volatile customer demands.
Publisher: MDPI AG
Date: 04-02-2020
DOI: 10.3390/APP10031007
Abstract: In this paper, we evaluate theoretical aspects of a distributed system of noncooperative robots controlled by a distributed model predictive control scheme, which operates in a shared space. Here, for collision avoidance, the future predicted state trajectories are projected on a grid and exchanged via discrete cell indexes to reduce the communication burden. The predicted trajectories are obtained locally by each robot and carried out in the continuous space. Therefore, the quantisation does not impose the quality of the solution. We derive sufficient conditions to show convergence and practical stability for the distributed control system by using an idea of a temporary roundabout derived from crossing patterns of street traffic rules, which is established in a fixed and flexible circle size. Furthermore, a condition for the sufficient prediction horizon length to recognise necessary detours is presented, which is adapted for the occupancy grid. The theoretical results match with the trajectory patterns from former numerical simulations, showing that this pattern is naturally chosen as an overall solution.
Publisher: IEEE
Date: 12-2018
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: MDPI AG
Date: 15-10-2019
DOI: 10.3390/APP9204331
Abstract: To deal with increasingly competitive challenges, today’s companies consider supplier performance as a crucial factor to their competitive advantage. Supplier development is one of the recent approaches to supplier performance enhancement and consistently requires relationship-specific investments. It is important to invest money, experts and/or machines in a supplier to minimize the risk of an inefficient supply chain while maximizing the level of profitability. This paper provides the number of optimization models to confront this issue utilizing Model Predictive Control. We consider a centralized and distributed setting with two manufacturers and one supplier, which enables us to simulate more realistic scenarios. We implement cooperative and non-cooperative scenarios to assess their impact on the manufacturers’ revenue. Results reveal that the cooperative setting between manufacturers pays off better than non-cooperative and collaborative settings in long-term investments. However, for short-term investments, the non-cooperative setting performs better than the others. We can conclude that, in short-term supplier development investments, an added value is generated since both the manufacturers and the supplier gain flexibility, therefore, investing separately can end up with higher profit for both manufacturers.
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: Springer International Publishing
Date: 11-11-2016
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier BV
Date: 09-2010
Publisher: Informa UK Limited
Date: 17-09-2018
Publisher: MDPI AG
Date: 08-08-2023
DOI: 10.3390/ELECTRONICS12163379
Abstract: This paper investigates the problem of trajectory tracking control in the presence of bounded model uncertainty and external disturbance. To cope with this problem, we propose a novel intelligent operator-based sliding mode control scheme for stability guarantee and control performance improvement in the closed-loop system. Firstly, robust stability is guaranteed by using the operator-based robust right coprime factorization method. Secondly, in order to further achieve the asymptotic tracking and enhance the responsiveness to disturbance, a finite-time integral sliding mode control law is designed for fast convergence and non-zero steady-state error in accordance with Lyapunov stability analysis. Lastly, the controller’s parameters are automatically adjusted by the proved stabilizing particle swarm optimization with the linear time-varying inertia weight, which significantly saves tuning time with a remarkable performance guarantee. The effectiveness and efficiency of the proposed method are verified on a highly nonlinear ionic polymer metal composite application. The extensive numerical simulations are conducted and the results show that the proposed method is superior to the state-of-the-art methods in terms of tracking accuracy and high robustness against disturbances.
Publisher: IEEE
Date: 09-2017
Publisher: Springer International Publishing
Date: 2018
Publisher: IEEE
Date: 12-2009
Publisher: Elsevier BV
Date: 03-2009
Publisher: Springer International Publishing
Date: 22-12-2015
Publisher: Wiley
Date: 03-02-2014
Publisher: Society for Industrial & Applied Mathematics (SIAM)
Date: 2010
DOI: 10.1137/090758696
Publisher: Elsevier BV
Date: 2016
Publisher: Elsevier BV
Date: 2011
Publisher: Springer Science and Business Media LLC
Date: 08-01-2022
Publisher: Walter de Gruyter GmbH
Date: 2008
Abstract: In the emulation approach to controller design for networked control systems the controller is first designed in continuous time ignoring the network and then implemented as a s led-data controller. While very attractive for its simplicity, typically sufficiently small s ling periods are needed in order to ensure satisfactory performance of the resulting s led-data closed loop. Thus, in the presence of network bandwidth constraints performance loss up to instability may occur. In this paper we present a variety of analytical and numerical techniques for the redesign of s led-data controllers which improve the s led-data performance of the non-redesigned controller and aim at reducing the necessary communication bandwidth.
Publisher: Springer International Publishing
Date: 15-09-2016
Publisher: Elsevier BV
Date: 2018
Publisher: Elsevier BV
Date: 2018
Publisher: Springer Science and Business Media LLC
Date: 08-11-2016
Publisher: Elsevier BV
Date: 07-2018
Publisher: Elsevier BV
Date: 07-2017
Publisher: Springer London
Date: 2011
Publisher: Elsevier BV
Date: 2016
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 07-2017
Publisher: Hindawi Limited
Date: 2018
DOI: 10.1155/2018/5935268
Abstract: A successful supply chain must be able to operate at the lowest cost while providing the best customer service as well as environmental protection. As industrial players are under pressure but mostly unprepared to take back products after their usage, logistics network design becomes an even more important issue. To allow for a maximum of flexibility and efficiency, we consider an integrated design of the forward/reverse logistics network using full delivery graph. We apply a Memetic Algorithm with a novel population generation to find a near optimal solution for large size problems. The effect of different parameters on the behavior of the proposed Metaheuristic Algorithm is investigated. Using the experimental work to find the best parameters for this problem is the outlook of these researches.
Publisher: Elsevier BV
Date: 2013
Publisher: MDPI AG
Date: 14-08-2019
DOI: 10.3390/ELECTRONICS8080896
Abstract: With the improvement in transportation infrastructure and in-vehicle technology in addition to a meteoric increase in the total number of commercial and non-commercial vehicles on the road, traffic accidents may occur, which usually cause a high death toll. More than half of these deaths occur due to a delayed response by medical care providers and rescue authorities. The chances of survival of an accident victim could increase drastically if immediate medical assistance is provided at an accident location. This work proposes a low-cost accident detection and notification system, which utilizes a multi-tier IoT-based vehicular environment principally, it uses V2X Communication and Edge/Cloud computing. In this work, vehicles are equipped with an On-Board Unit (OBU) in addition to mechanical sensors (accelerometer, gyroscope) for reliable accident detection along with a Global Positioning System (GPS) module for identification of accident location. In addition to this, a camera module is implanted on the vehicle to capture the moment when an accident takes place. In order to facilitate inter-vehicle communication (IVC), OBU in each vehicle incorporates a wireless networking interface. Once an accident occurs, a vehicle detects it and generates an alert message. It then sends the message along with the accident location to an intermediate device, placed at the edge of the vehicular network, and therefore called an edge device. Upon receiving the notification, this edge device finds the nearest hospital and makes a request for an ambulance to be dispatched immediately. It also performs some preprocessing of data and effectively acts as a bridge between the sensors installed inside the vehicle and the distant server deployed in the cloud. A significant issue that the traffic authorities are currently facing is the real-time visualization of data obtained through such environments. Wireless interfaces are usually capable of forwarding real-time sensor data however, this feature is not yet commercially available in the OBU of the vehicle therefore, practical implementation is carried out using the Internet of things (IoT) in order to create a network among the vehicles, the edge node, and the central server. By performing analysis on the adequate acquired data of road accidents, the constructive plans of action can be devised that may limit the death toll. In order to assist the relevant authorities in performing wholesome analysis of refined and reliable data, a dynamic front-end visualization is proposed, which is hosted in the cloud. The generated charts and graphs help the personnel at relevant organizations to make appropriate decisions based on the conclusive analysis of processed and stored data.
Publisher: Springer International Publishing
Date: 15-09-2016
Publisher: Springer International Publishing
Date: 2014
Publisher: Springer International Publishing
Date: 2018
Publisher: IEEE
Date: 12-2012
Publisher: Springer International Publishing
Date: 2018
Publisher: Springer International Publishing
Date: 2018
Publisher: MDPI AG
Date: 29-12-2022
DOI: 10.3390/APP13010449
Abstract: Nowadays, quickly changing customer demands are a big challenge in the manufacturing industry, especially for job shops, which are typical coupling and nonlinear multi-input–multi-output (MIMO) systems. In order to achieve good shop floor performance in the presence of short-term demand fluctuations, a key performance indicator—work in process (WIP)—is required to be effectively controlled in the vicinity of the desired levels. For this purpose, a machinery-oriented capacity adjustment approach via a reconfigurable machine tool (RMT) is employed to flexibly balance capacity and load in the case of a bottleneck. A mathematical model concerning the RMT and WIP was first established in the presence of uncertainty and delays. The operator-based robust right coprime factorization (RRCF) method was adopted to stabilize the uncertain system, and adaptive integral separated proportional–integral (ISPI) tracking controllers were further designed to improve the transient and robustness performance. The performance of the proposed ISPI-RRCF was analyzed and compared with that of a state-of-the-art method in a simulation. The results showed that both control systems could ensure that the WIP was within an allowed bound, while the former had lower overshoots, shorter setting times, and more concentrated distributions facing stochastic demands. This further indicated the effectiveness of the proposed algorithm in the avoidance of serious bottlenecks and unbalanced capacity distributions.
Publisher: Inderscience Publishers
Date: 2018
Publisher: Informa UK Limited
Date: 28-10-2022
Publisher: Springer Berlin Heidelberg
Date: 2007
Publisher: Elsevier BV
Date: 03-2021
Publisher: Elsevier BV
Date: 2012
Publisher: Elsevier BV
Date: 07-2017
Publisher: Springer International Publishing
Date: 2018
Publisher: Elsevier BV
Date: 2011
Publisher: Springer Science and Business Media LLC
Date: 07-11-2016
Publisher: MDPI AG
Date: 05-03-2020
DOI: 10.3390/PR8030300
Abstract: Supplier development constitutes one of the current tools to enhance supply chain performance. While most literature in this context focuses on the relationship between manufacturers and suppliers, supplier development also provides an opportunity for distinct manufacturers to collaborate in enhancing a joint supplier. This article proposes a model for the optimization of such joint supplier development programs, which incorporates the effects of trust in the manufacturer-to-manufacturer relationship. This article uses a model-predictive formulation to obtain optimal supplier development investment decisions to consider the strong dynamics of the markets. Thereby, the model is designed to be highly customizable to the needs and requirements of different companies. We analyzed the price development related to Mercedes’ A-Class cars and the cost development in the automotive sector over the last ten years in Germany. According to the obtained result, the proposed model shows a sensible behavior in including trust and its effects in supplier development, even when just applying a set of generalized rules. Moreover, the numeric experiments showed that aiming for a balanced mix of optimizing revenue and trust results in the highest revenue obtained by each partner.
Location: United Kingdom of Great Britain and Northern Ireland
Location: Germany
No related grants have been discovered for Jürgen Pannek.