Assessment of Energy Efficiency in Lean Transformation: A Simulation Based Improvement Methodology

Author(s):  
Serdar Baysan ◽  
Emre Cevikcan ◽  
Şule Itır Satoglu
Author(s):  
Valerio De Martinis ◽  
Ambra Toletti ◽  
Francesco Corman ◽  
Ulrich A. Weidmann ◽  
Andrew Nash

The optimization of rail operation for improving energy efficiency plays an important role for the current and future market of rail freight services and helps rail compete with other transport modes. This paper presents a feedforward simulation-based model that performs speed profile optimization together with minor rescheduling actions. The model’s purpose is to provide railway operators and infrastructure managers with energy-efficient solutions that are tailored especially for freight trains. This work starts from the assumption that freight train characteristics are completely defined only a few hours before actual departure; therefore, small specific feedforward adjustments that do not affect the surrounding operation can still be considered. The model was tested in a numerical example. The example clearly shows how the optimized solutions can be evaluated with reference to energy saved and robustness within the rail traffic. The evaluation is based on real data from the North–South corridor crossing Switzerland from Germany to Italy.


2018 ◽  
Vol 51 (2) ◽  
pp. 689-694 ◽  
Author(s):  
Bernhard Heinzl ◽  
Philipp Raich ◽  
Franz Preyser ◽  
Wolfgang Kastner

2020 ◽  
Vol 4 (3) ◽  
pp. 94
Author(s):  
Thomas Sobottka ◽  
Felix Kamhuber ◽  
Bernhard Heinzl

This paper presents the development and evaluation of a digital method for multi-criteria optimized production planning and control of production equipment in a case-study of an Austrian metal casting manufacturer. Increased energy efficiency is a major requirement for production enterprises, especially for energy intensive production sectors such as casting. Despite the significant energy-efficiency potential through optimized planning and the acknowledged application potential for sophisticated simulation-based methods, digital tools for practical planning applications are still lacking. The authors develop a planning method featuring a hybrid (discrete-continuous) simulation-based multi-criteria optimization (a multi-stage hybrid heuristic and metaheuristic method) for a metal casting manufacturer and apply it to a heat treatment process, that requires order batching and sequencing/scheduling on parallel machines, considering complex restrictions. The results show a ~10% global goal optimization potential, including traditional business goals and energy efficiency, with a ~6% energy optimization. A basic feasibility demonstration of applying the method to synchronize energy demand with fluctuating supply by considering flexible energy prices is conducted. The method is designed to be included in the planning loop of metal casting companies: receiving orders, machine availability, temperature data and (optional) current energy market price-data as input and returning an optimized plan to the production-IT systems for implementation.


2017 ◽  
Vol 139 ◽  
pp. 450-455 ◽  
Author(s):  
Yassine Kharbouch ◽  
Abdelaziz Mimet ◽  
Mohammed El Ganaoui

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