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  <doc>
    <id>3791</id>
    <completedYear/>
    <publishedYear>2014</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>5</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>IEEE</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Evaluation of thermal solder joint quality and thermal performance of PCBs by using standard measurement equipment</title>
    <abstract language="eng">By using more powerful LEDs a good thermal management is becoming more and more important. Here usually the thermal interconnects have to be in focus. Therefore a simple and rapid measurement method for the thermal check of the solder joint in a high volume production is necessary. A standard thermal resistance measurement is very time consuming due to the calibration of each device. By using thermal characterized reference devices it is possible to skip the time consuming part. Furthermore, a simple methodology for evaluating the thermal performance of the various metal core PCB (MCPCB) materials and construction is required during development. In this paper we will present how we successfully demonstrated that this new method offers an opportunity to determine the thermal performance of a high power QFN LED on different types of isolated metal substrate (IMS) and with a standard SMU [1] (source measurement units).</abstract>
    <parentTitle language="eng">20th International Workshop on Thermal Investigations of ICs and Systems, 24-26 Sept. 2014, Greenwich, UK</parentTitle>
    <identifier type="doi">10.1109/THERMINIC.2014.6972522</identifier>
    <enrichment key="opus.import.date">2022-04-28T19:43:52+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Keine Lizenz - Es gilt das deutsche Urheberrecht: § 53 UrhG</licence>
    <author>Sebastian Schlal</author>
    <author>Markus Wicke</author>
    <author>Thomas Zahner</author>
    <author>Kurt-Jürgen Lang</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Electrical resistance measurement</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Light emitting diodes</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Semiconductor device measurement</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Soldering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>standards</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Thermal resistance</value>
    </subject>
    <collection role="institutes" number="FakEI">Fakultät Elektro- und Informationstechnik</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
  <doc>
    <id>8176</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1677</pageFirst>
    <pageLast>1678</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>University of Hawaii at Manoa</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>2025-01-07</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Introduction to the Minitrack on Simulation Modeling, Artificial Intelligence and Digital Twins for Decision Making in Production and Logistics</title>
    <abstract language="eng">The minitrack contains contributions with a focus on simulation modeling and digital twins and decision making in the context of Industry 4.0. The use of simulation models and digital twins is manifold, from planning to virtual commission and real-time operational decision support. Cyber-physical systems integrate the real world and the virtual world to enable decision making in the age of Industry 4.0. &#13;
For example, customer decisions and supply disruptions which directly influence manufacturing and logistics systems require immediate decisions. Thus, models must have the capability to support decision making in manufacturing as well as in internal and external logistics in real-time. Methods include discrete-event simulation, discrete-rate simulation, hybrid simulation, system dynamics simulation, the combination of simulation modeling with machine learning or optimization heuristics, prescriptive analytics, and adaptive systems. Furthermore, this minitrack addresses simulation education and simulation models and digital twins used for education and training in manufacturing and logistics.</abstract>
    <parentTitle language="eng">Proceedings of the 58th Hawaii International Conference on System Sciences, January 7-10, 2025, Honolulu, Hawaii</parentTitle>
    <identifier type="doi">10.24251/HICSS.2025.205</identifier>
    <identifier type="handle">https://hdl.handle.net/10125/109045</identifier>
    <identifier type="isbn">978-0-9981331-8-8</identifier>
    <enrichment key="opus.import.date">2025-06-03T21:49:53+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Steffen Strassburger</author>
    <author>Stefan Galka</author>
    <author>Sebastian Lang</author>
    <author>Tobias Reggelin</author>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="oaweg" number="">Gold Open Access- Erstveröffentlichung in einem/als Open-Access-Medium</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <collection role="institutes" number="">Innovationszentrum für Produktionslogistik und Fabrikplanung (IPF)</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
  </doc>
  <doc>
    <id>3384</id>
    <completedYear/>
    <publishedYear>2021</publishedYear>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst>1643</pageFirst>
    <pageLast>1644</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>University of Hawai'i at Manoa Hamilton Library</publisherName>
    <publisherPlace>Honolulu, HI</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Introduction to the Minitrack on Modeling and Decision Making in Manufacturing and Logistics in the Age of Industry 4.0</title>
    <abstract language="eng">The minitrack contains contributions with a focus on modeling and decision making in manufacturing and logistics in the context of Industry 4.0. &#13;
Cyber-physical systems integrate the real world and the virtual world. For example, customer decisions and supply disruptions which directly influence manufacturing and logistics systems require immediate decisions in terms of planning and controlling the manufacturing and logistics systems. In order to immediately respond to these dynamics, models must have the capability to support decision making in manufacturing as well as in internal and external logistics in real-time. Two of the Mintrack papers describe concepts and models for digital twins. One paper provides an adaptive scheduling framework for solving multi-objective hybrid flow shop scheduling problems and one paper investigates matrix production systems and with their requirements and impacts on logistics planning.</abstract>
    <parentTitle language="deu">Proceedings of the 54th Hawaii International Conference on System Sciences (HICSS): 2021 Hawaii, USA</parentTitle>
    <identifier type="isbn">978-0-9981331-4-0</identifier>
    <identifier type="doi">10.24251/HICSS.2021.198</identifier>
    <enrichment key="opus.import.date">2022-04-08T07:23:56+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Tobias Reggelin</author>
    <author>Stefan Galka</author>
    <author>Dmitry Ivanov</author>
    <author>Sebastian Lang</author>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
  </doc>
  <doc>
    <id>4043</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1964</pageFirst>
    <pageLast>1973</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>2022</volume>
    <type>conferenceobject</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2022-01-01</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Developing a Decision Support System for Integrated Decision-Making in Purchasing and Scheduling under Lead Time Uncertainty</title>
    <abstract language="eng">Decision-making in supply chain management is complex because of the relations between planning tasks from different stages and planning levels. Uncertainties such as unpredictable supplier lead times and supply chain disruptions further complicate decision-making. Considering the case study of a company in printed circuit board assembly, a three-level concept is proposed that includes a decision support system. The global single-source supply network is characterized by highly variable lead times. Hence, the company maintains high inventory levels to prevent running out of stock. The decision support system considers the purchasing and scheduling decision problems in an integrated way. The prototypical implementation of the purchasing algorithm uses a genetic algorithm that recommends reorder days and order quantities using a simulation model. In addition, it evaluates the risks of the recommended solution by calculating the probability of stockouts for each order cycle.</abstract>
    <parentTitle language="deu">Proceedings of the 55th Hawaii International Conference on System Sciences (HICSS55): January 3-7, 2022, Maui, Hawaii, USA</parentTitle>
    <identifier type="doi">10.24251/HICSS.2022.247</identifier>
    <identifier type="handle">http://hdl.handle.net/10125/79579</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Benjamin Rolf</author>
    <author>Tobias Reggelin</author>
    <author>Sebastian Lang</author>
    <author>Stefan Galka</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>decision support system</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simulation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>supply chain optimization,</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>purchasing</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>cyber-physical system</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Industry 4.0</value>
    </subject>
    <collection role="ddc" number="5">Naturwissenschaften und Mathematik</collection>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <collection role="oaweg" number="">Diamond Open Access - OA-Veröffentlichung ohne Publikationskosten (Sponsoring)</collection>
  </doc>
  <doc>
    <id>8206</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1647</pageFirst>
    <pageLast>1648</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>conferenceobject</type>
    <publisherName>ScholarSpace</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Introduction to the Minitrack on Simulation Modeling and Digital Twins for Decision Making in the Age of Industry 4.0</title>
    <abstract language="eng">The minitrack contains contributions with a focus on simulation modeling and digital twins and decision making in the context of Industry 4.0. The use of&#13;
simulation models and digital twins is manifold, from planning to virtual commission and real-time operational decision support. Cyber-physical systems integrate the real world and the virtual world to enable decision making in the age of Industry 4.0.&#13;
For example, customer decisions and supply disruptions which directly influence manufacturing and logistics systems require immediate decisions.&#13;
Thus, models must have the capability to support decision making in manufacturing as well as in internal and external logistics in real-time.&#13;
Methods include discrete-event simulation, discrete-rate simulation, hybrid simulation, system dynamics simulation, the combination of simulation&#13;
modeling with machine learning or optimization heuristics, prescriptive analytics, and adaptive systems. Furthermore, this minitrack addresses&#13;
simulation education and simulation models used for education and training in manufacturing and logistics.</abstract>
    <parentTitle language="eng">Proceedings of the 57th Hawaii International Conference on System Sciences (HICSS), January3-6, 2024, Honolulu, Hawaii</parentTitle>
    <identifier type="isbn">978-0-9981331-7-1</identifier>
    <identifier type="doi">10.24251/HICSS.2024.206</identifier>
    <identifier type="handle">hdl.handle.net/10125/106584</identifier>
    <enrichment key="opus.import.date">2025-06-03T21:49:53+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">importuser</enrichment>
    <enrichment key="BegutachtungStatus">peer-reviewed</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Stefan Galka</author>
    <author>Steffen Strassburger</author>
    <author>Sebastian Lang</author>
    <author>Tobias Reggelin</author>
    <collection role="institutes" number="FAKMB">Fakultät Maschinenbau</collection>
    <collection role="othforschungsschwerpunkt" number="16316">Produktion und Systeme</collection>
    <collection role="DFGFachsystematik" number="1">Ingenieurwissenschaften</collection>
  </doc>
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