Skip to main content

2024 | Book

Energy-Related Material Flow Simulation in Production and Logistics

Editors: Sigrid Wenzel, Markus Rabe, Steffen Strassburger, Christoph von Viebahn

Publisher: Springer International Publishing


About this book

This book provides for the first time an overview on the current approaches and applications of energy aspects in production and logistics by the use of simulation techniques. During the last decade, the importance of energy in the material flow processes has become more and more important. The pressure to reduce the environmental footprint of production and logistics systems will even intensify in future. Therefore, enterprises have started to integrate the use of energy into their planning processes much more than before, even designing feedback loops, e.g., from energy control to production control. This receives additional attention with the increasing use of renewable, but less reliable, energy sources. Care must be taken to establish processes that aim to use energy when it is available. As an example, many industrial processes like melting or coating have significant energy demands, but could vary the point of time of its consumption within specific limits, leading to a very high complexity. ​

It discusses the construction and application of energy-specific performance indicators and analyzes the input information that needs to be acquired before implementing suitable models. On this basis, concrete technical solutions are introduced.

Table of Contents


General Considerations

Chapter 1. Classification, Input Data, and Key Performance Indicators
Simulation is a well-known technology for production and logistics, especially for the planning of new systems and the examination of ideas to optimize existing ones. In the past, the main target of such studies has been costs of equipment and personnel, but the continuously stricter view on consumption of energy has shifted this focus towards the analysis of energy consumption and emission of greenhouse gas. In some cases this might be straightforward, e.g., when the resulting production hours can just be multiplied with energy consumption per hour. Many cases, however, are far more complicated and can only be sufficiently analyzed when the detailed dynamics of energy consumption are already considered in the simulation model. Thus, a number of different approaches exist to model energy aspects in simulation models, depending on the goal of the investigation and the kind of production or logistics process. This chapter classifies these approaches in a morphological box and explains the details of the related categories. Furthermore, it discusses the requirements to input data that arise when simulation models are amended with energy components, and discusses the additional results that can be gained from such models.
Markus Rabe, Johannes Stoldt, Steffen Strassburger, Christoph von Viebahn

Application Fields

Chapter 2. Manufacturing
The manufacturing industry is responsible for a large share of global environmental impacts (e.g., greenhouse gas emissions) that can mainly be tracked back to energy demand. This energy demand is determined by a diversity of processes and machines, which dynamically interact in process chains and with other factory elements such as technical building services (TBS). Given that, system-oriented material flow simulation with inclusion of energy aspects bears the potential to support the energy transition of industry through fostering both energy efficiency and substitution towards renewable resources. The chapter addresses the necessary background as well as common aspects in the context of energy-oriented manufacturing system simulation. Four manufacturing case studies underline the feasibility and potential of available simulation approaches for improving energy-related environmental impacts and also costs. Additionally, an outlook towards potential future research steps is given.
Sebastian Thiede, Antal Dér, Marc Münnich, Thomas Sobottka
Chapter 3. Automotive
The automotive industry is an important branch in many industrialized countries in Europe, the USA, Japan, and China. Recent political developments provide challenges to achieve carbon–neutral production and to switch from combustion engines to electric engines or other alternative fuels. This is also reflected in the development of simulation in production and logistics, where energy-related questions became more present in recent years. In this chapter, data from the ASIM working group about related literature are analyzed. Topics and architectures already being examined in energy simulation in the automotive industry are reviewed. The developments are illustrated by two application cases. The first use case shows the importance of simulating the power consumption and charging strategies of automated guided vehicles on the performance of the material flow system. The second example shows the possibilities of integrating complex thermodynamic processes into the material flow simulation by combining continuous and discrete models. The chapter ends with a short conclusion on the state of the art regarding energy simulation in the automotive sector.
Tim Peter, Kristina Sokoll, Wolfgang Schlüter, Johannes Dettelbacher
Chapter 4. Transportation
With the evolution of emerging technologies, transportation systems are becoming increasingly complex. At the same time, the advent of grand environmental challenges, such as climate change, requires researchers and practitioners to develop new transportation strategies that ensure a high degree of energy efficiency. Due to their immanent capabilities to study the behavior of complex systems over time, simulation methodologies can provide valuable assets to determine the energy efficiency on a transportation system. Thus, this chapter reviews the current state of the art regarding energy-related simulation research in the transportation sector. It outlines the status quo of energy-related simulation research and provides an overview on the most common simulation methods used for analyzing energy-related transportation aspects such as vehicle emissions. Moreover, to demonstrate the practical applicability of simulation in this domain, two exemplary use cases are elaborated, employing an agent-based modeling technique to assess emission implications resulting from different freight and grocery transportation strategies. The results of the use cases show that simulation can be a powerful methodology to evaluate energy-related transportation effects, ultimately supporting more informed theory construction and strategy formulation incentives.
Marvin Auf der Landwehr, Javier Faulin, Adrian Serrano-Hernandez
Chapter 5. Retail
In the last decades, companies in the retail sector have faced growing customer demands for convenient delivery of products combining the alternatives of traditional in-store shopping and online shopping providing home deliveries or pickups at specific pickup locations, along with global aims to reduce energy consumption and CO2 emissions worldwide with respect to the global climate change. Targets to reduce emissions are supported by a majority of the world’s societies and companies. Especially retailers are characterized by very high transportation volumes with often very small transportation lot sizes. Here, distribution networks need to be designed that allow low energy consumption while still addressing customer demands. Simulation has been a core method to analyze such networks and underlying processes with respect to costs, but also enables detailed analyses of the energy consumption and CO2 emissions of such systems. This chapter gives an overview of the scope and objectives for retail distribution systems and present challenges for respective simulation models, both addressing Discrete Event Simulation and System Dynamics. Furthermore, it presents three application studies and gives an outlook to future research and applications.
Kai Gutenschwager, Markus Rabe, Michael E. Kuhl, Jorge Luis Chicaiza-Vaca
Chapter 6. Perishables
Perishable goods such as fruits and vegetables require timely and accurate handling routines to ensure a high degree of product quality across all stages of the supply chain. Consequently, they constitute a fundamental business factor for organizations that needs to be managed in a delicate and prudent fashion. The perishability of products characterizes a challenging environment that requires dynamic planning and evaluation approaches to avoid or countervail the negative energetic impacts of inefficient operations. By providing a sophisticated conceptualization of the given system and its dynamic evolution over time, computer simulation serves as viable tool for analyzing and optimizing energy-related aspects of production and logistics systems for perishable items. This chapter reviews the current state of research for simulating energy-related aspects of perishable products and highlights common energy performance indicators such as food waste, emissions, and temperature. To outline contextual interdependencies and provide practical insights into the use of simulation to assess energy aspects of perishables, three use cases are presented. These cases elaborate on the energetic implication of a juice production plant in Sweden, the estimation of food quality losses in regional strawberry supply chains in Austria, and the energy and media consumption of a beverage bottling plant in Germany.
Christian Fikar, Björn Johansson, Karsten Beyer, Marvin Auf der Landwehr
Chapter 7. Renewables
In order to reduce greenhouse gas emissions and energy costs, renewable energy sources are of growing importance for manufacturing systems. This chapter gives an outline of different renewables, the complexities that arise from their use, and explains how simulation studies can be applied to address the interactions between manufacturing systems and renewables. To give examples of the challenges of integrating renewables in manufacturing, two applications are presented for simulation in the design and evaluation of manufacturing control strategies under constraints of renewable energy sources. The simulation models include several forms of renewable energy sources, manufacturing resources as well as an energy storage. In these applications, the simulation serves two different purposes. In the first study, the simulation is used to generate training data for an AI algorithm based on multi-agent reinforcement learning. This algorithm is applied to a closely linked manufacturing and energy system in order to balance energy supply and demand. The second application presents how a customized energy tool for a commercial material flow simulation can be used to generate high-resolution load forecasts applying scenarios for order scheduling. Based on the simulation result, the best scheduling alternative for a given energy supply by renewables can be chosen.
Cedric Schultz, Martin Rösch, Lukas Bank
Energy-Related Material Flow Simulation in Production and Logistics
Sigrid Wenzel
Markus Rabe
Steffen Strassburger
Christoph von Viebahn
Copyright Year
Electronic ISBN
Print ISBN

Premium Partners