Research

The planning of logistics centres is a complex, low-structured decision-making problem whose goal orientation and processing is carried out by interdisciplinary collectives. A mathematically optimal solution to the planning problem does not exist - the goal of planning can only be to find the best possible solution. A crucial task of systematic planning is to overcome the structural deficits. This is done by decomposing the problem into sub-problems as well as modelling and abstracting the (sub-)problems. From the fact of the structural deficits it also follows that the legitimacy of the planning result results from the intersubjectivity of the heuristics used.

Against this background, the thesis deals with the determination of a procedure for the concept planning of logistics centres. For the elaboration, a consensus-oriented science theory in combination with a critical hermeneutic research method is chosen. For this purpose, relevant basics of systems theory in general and systems engineering in particular are first identified. Together with basics of model theory and model-based systems engineering as a discipline that emphasises modelling as a central task along the system design process, requirements for the structure, content and documentation of a process model are defined.

Subsequently, the Distribution Centre Design Process (DCDP) is developed. Along an eight-step process, starting with the task and objective, solution concepts of logistics centres are developed and evaluated. The process is divided into two parts, each with four phases: a functional design part, in which the task is transformed into a functional concept in the sense of a top-down problem analysis, and a physical design part, which transforms this concept into one or more evaluated solution proposals through a bottom-up solution synthesis.

In particular, the formalisation of the functional area of logistics centre planning, which has not been considered scientifically so far, is focused on. This results, among other things, in the definition of 18 services and 15 basic transformation properties of handling units. These can be used to create and semantically test so-called service flow networks, which describe the functional sequence and transformations of the service objects in logistics centres. The conceptual models used in the sub-steps of the phases are described and documented using SysML. Central relationships are then formalised by means of discrete modelling.

Finally, the results are subjected to a critical review based on the principles of proper modelling and applied to a practical example. The regularity of the models is confirmed and their suitability for practice is demonstrated.

Full Dissertation

Send E-Mail

In an era of personalized services and products, logistics is tasked with identifying things informationally beyond the physical movement of goods and connecting them in global supply chains. “Tracking&Tracing” is a basic requirement in the context of logistic system planning and control to ensure the availability of the right information in real time for all goods. Intelligent data processing in the form of distributed algorithms poses a particular challenge for the dynamic (self-)control of goods flows.

Material flow system planning is traditionally based on a pre-planned, maximum flow (marginal performance consideration) at specific points of a system. However, the continuous flow of goods is influenced by incoming events, which can result in an alarming deviation from the plan, and the performance's ex ante planned controllability is reduced to absurdity. This has an impact on the entire supply chain depending on where events occur. This includes logistics centers, which must respond to events in a particularly flexible and active manner. The high volume of traffic at large transshipment hubs causes increased material flow disruptions: trucks are delayed, internal resources and system loads fluctuate, and connecting transports and capacities change on short notice. A method for planning and controlling the material flow as an ad hoc reaction to events is required to manage the complexity of the material flow.

Employees of a logistics center typically learn about disruptions after they have occurred, making it nearly impossible to mitigate them. The logistics center in the supply chain is particularly vulnerable to both the dynamics and the lack of transparency of the flow of information and materials. Employees must adapt to constantly changing situations caused by unforeseeable events and make far-reaching and complex decisions in a short period of time.

The event- and resource-oriented approach for dynamic scheduling of logistics objects is the focus of the multi-agent system (EventPlan) developed in the context of this thesis in a logistics node. The system assists the logistics decision maker in making an adequate decision in a limited amount of time. Orders are reprioritized and rescheduled as a result, or resources are reallocated. The decision is not made by the person in charge, but he is supported by the results of the analysis. The responsible employee always makes the final decision on possible actions, such as the use of additional resources.

Practicality necessitates the development of a scalable, transferable method for dynamic, near-real-time scheduling of orders and resources, capable of processing events in near-real time and autonomously triggering follow-up actions. For these reasons, a decentralized communication and control algorithm based on a multi-agent system is being developed and validated using highly dynamic air freight logistics.

Full Dissertation

Send an E-Mail

For years, the logistical focal point of order picking has been subject to an increasing complexity trend. The variety of technology variants and organizational forms is constantly expanding. Dynamic system characteristics and performance-inhibiting interactions are increasingly becoming decisive planning aspects in the case of heterogeneously structured overall systems composed of different technology systems.

Questions about dynamic behavior cannot be answered accurately using the statically dominated planning and calculation methods used today in the concept planning phase. This lack of planning quality raises the possibility of incorrect dimensioning of dynamic-dependent components, which leads to errors in selecting a preferred variant.

This problem can be solved using simulation technology. This is currently only used in the detailed planning phase for functional verification of a chosen preferred variant. As an example, in the current work, a concept for the efficient use of simulation was developed and implemented while still in the concept planning phase. The goal was to improve the quality of the planning results without the extra effort that simulation requires.

Standardized planning and simulation models, modeling methods, and data structures for heterogeneously structured picking systems were created for this purpose. A modeling paradigm was included, as well as standard building blocks and objects of heterogeneously structured picking systems. Another component was the creation of simulation models, structures, and elements that were generated automatically.

The methods were integrated into a planning environment that assists the planner throughout the simulation-based concept planning process.

The validation performed based on an application example revealed that early simulation integration results in a significant increase in the quality of planning and results.

This is especially true for dynamic-dependent dimensioning aspects such as buffer capacities, resource dimensioning, and downstream technology dimensioning. Furthermore, a planner in the concept planning phase gains a high degree of transparency and understanding of the dynamic behavior of the considered model variants. The general feasibility of incorporating early simulation into the planning process has been demonstrated in this work, and challenges and limitations have been identified.

The use of simulation technology in the concept planning phase of heterogeneously structured order picking systems will become more established in the future through additional research and development activities.

Full Dissertation

Send an E-Mail

Logistics centers, as an essential component of a supply chain, are constantly changing. Flexibility, adaptability, and proactivity are becoming increasingly important in order to run logistics centers efficiently in the long run. As a result, it is critical to be able to assess the sensitivity of their performance.

Operating characteristic curves are developed in this work to map the performance of logistics centers. This is described by key figures that take the dynamic environment into account and are dependent on an influencing variable. The operating characteristic curves are produced by varying the influencing variable.

The key figures used to map the operating characteristics are derived mathematically and are based on statistical formulas that are transferred to the logistics center in central aspects. The key figures are the service level, the delivery time, the inventory of resources, and the logistics costs. A model is created to represent the complex operational processes of a logistics center and to determine key figures. Finally, a procedure for implementing the model is presented. The operating characteristic curves are determined for various typical logistics centers to demonstrate the potential applications.

Furthermore, various factors that can affect the performance of logistics centers are discussed. This thesis' research is focused on the fashion industry. This is especially appropriate because it exhibits high fluctuations and pronounced seasonality, which is representative of other industries in terms of logistics.

Full Dissertation

Send an E-Mail