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  <doc>
    <id>232</id>
    <completedYear/>
    <publishedYear>2012</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2020-01-29</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">A simulation analysis of Independent Requirements Consumption in Master Production Scheduling</title>
    <abstract language="eng">This  poster  presents  purpose  and  function  of  the  Independent  Requirements  Consumption  in Master Production Scheduling and gives recommendations for its application. The approach of hierarchical production planning and its planning problems are explained. The problem of new customer  requirements  information  between  planning  periods  and  solving  options  are  shown. The solving option of Independent Requirements Consumption is focus of this poster. The algorithm of the Independent Requirements Consumption that is implemented in commercial Enterprise Resource Planning (ERP) systems like the SAP system is analyzed. The methods for analyzing the effects of the Independent Requirements Consumption are outlined. The scenarios for simulation studies are stated and compared  to  similar  investigations.  The simulation studies were performed on a simulation  system  at IPF that contains both a production planning and control system and a production. The extent of simulation analyses outreaches similar investigations, especially because of the variety of scenarios. For scenarios in which capacity is available to a sufficient extent, advice for setting the Independent Requirements Consumption parameters is given. It is pointed out that with production constrained scenarios, the necessity to level out production  leads to problems. An algorithm to determine necessary  inventory levels is presented. It is stated that straight advice for  Independent Requirements Consumption parameter settings might not be possible with production constrained scenarios. Further analyses with production constrained scenarios as well as investigations concerning safety stocks in combination with Independent Requirements Consumption are current and future research topics at the Innovation Center for Production Logistics and Factory Planning.</abstract>
    <parentTitle language="eng">ASIM Workshop, Trends in Computational Science and Engineering (ASIM TCSE 2012), February 13-14, 2012, Vienna University of Technology, Austria</parentTitle>
    <author>Julian Englberger</author>
    <author>Frank Herrmann</author>
    <author>Thorsten Claus</author>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Produktonsplanung</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Simulation analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Independent Requirements Consumption</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Master Production Scheduling</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Enterprise-Resource-Planning</value>
    </subject>
    <subject>
      <language>deu</language>
      <type>swd</type>
      <value>Kundenorientierung</value>
    </subject>
    <collection role="ddc" number="67">Industrielle Fertigung</collection>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
  <doc>
    <id>7893</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-01-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">An Optimization Model for Production Scheduling with Energy Consumption and Energy-related Emissions</title>
    <abstract language="eng">Due to the scarcity of resources, rising costs as well as the further need for ecological improvement in industrial production, firms are increasingly motivated to take into account energy consumption in production planning. Associated with this, the consideration of energy-related emissions is becoming an additional point of interest for decisionmakers in both, economic and ecological terms. Based on an extensive systematic literature review, the study at hand presents a multicriterial scheduling problem that addresses tardiness, energy consumption and energy-related emissions in production scheduling. A &#13;
model is introduced that takes into account job release dates, multiple machine states, a power demand threshold as well as time-varying emission conversion factors. Multiple case studies are analysed and the effects of different technological implementations as energy onsite generation and energy storage systems are evaluated. Furthermore, several price mechanisms regarding energy procurement and emission trading are discussed. Moreover, by coupling the optimization model&#13;
to a discrete event simulation model, we are able to compare the model results to real case scenarios. First computational experiments have demonstrated that the model and its extensions can effectively reduce the environmental impact associated with production while simultaneously considering corresponding economic objectives. Based on the proposed approach, our research aims on answering the question with which economic trade-offs an ecological improvement in terms of energy consumption and emission output can be achieved in production.</abstract>
    <parentTitle language="eng">OR 2022, International Conference on Operations Research 2022, September 6-9, 2022,  Karlsruhe</parentTitle>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">true</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Hajo Terbrack</author>
    <author>Thorsten Claus</author>
    <author>Frank Herrmann</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Production Scheduling</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Energy Consumption</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
  <doc>
    <id>7890</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferencepresentation</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-01-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Aggregate Production Planning under Risk of Disruption</title>
    <abstract language="eng">In recent years, large scale disruptions to global supply chains, like the Covid pandemic, a ship blocking the Suez canal or sanctions against Russia, have caused production to slow down or even to stand still, causing shortages and massive losses for affected businesses. Even if only specific companies were originally affected, shortages and delays rippled along the supply network.&#13;
The established approach to deal with disruptions is to utilize safety stock and capacity to compensate for fluctuations in uncertain quantities like customer demand. This approach is tried and tested for small fluctuations. To address larger disruptions, like the above given, very high safety stock and capacity would be needed, which would lead to unnecessarily high costs.&#13;
Resilience has often been viewed as an expensive capability that drives costs. Recent studies however advocate for the development of lean resilience concepts, creating new capabilities, which enable resilience and can deal with large fluctuations, reimagining resilience from the perspectives of efficiency and value creation.&#13;
This contribution identifies gaps in current research and establishes structural deficits of approaches discussed in the literature regarding supply chains. Firstly, the need for rigorous, quantitative definitions of resilience and relevant disruptions is justified.&#13;
Then, a stochastic model for aggregate production planning that includes capabilities to compensate for such large fluctuations along several dimensions is proposed. Lastly, this model is then applied to a case study pertaining to a realistic supply chain under the risk of large scale disruptions and the results of this approach are evaluated.</abstract>
    <parentTitle language="eng">OR 2024, International Conference on Operations Research 2024, September 3-6, 2024, Munich</parentTitle>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Frank Herrmann</author>
    <author>Maximilian Schoen</author>
    <author>Thorsten Claus</author>
    <author>Chenghao Dai</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Supply Chain Resiliance</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Aggregate Production Planning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Supply Chain Disruption</value>
    </subject>
    <collection role="institutes" number="FakIM">Fakultät Informatik und Mathematik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
</export-example>
