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  <doc>
    <id>1923</id>
    <completedYear>2024</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>73</pageFirst>
    <pageLast>78</pageLast>
    <pageNumber>6</pageNumber>
    <edition/>
    <issue/>
    <volume>122</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
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    <title language="eng">Efficient data acquisition for traceability and analytics</title>
    <abstract language="eng">Implementing processes for traceability is required in various industries to assure product quality during manufacturing, provide evidence on required processing conditions or facilitate product recalls. Commonly, radio-frequency identification (RFID) or code recognition techniques (e.g. Data Matrix) are applied to track the flow of workpieces through a manufacturing system and link processing data accordingly. Although the analysis of tracking data is well-examined, we still see a gap in the research on the trade-off between data acquisition, data analytics and data quality. Here, we present a framework to increase the value of existing data by enabling data analytics while addressing common pitfalls and reducing the costs of data management.</abstract>
    <parentTitle language="eng">Procedia CIRP</parentTitle>
    <identifier type="issn">2212-8271</identifier>
    <identifier type="urn">urn:nbn:de:kobv:526-opus4-19232</identifier>
    <enrichment key="opus.import.data">@articleREINHARDT202473, title = Efficient data acquisition for traceability and analytics, journal = Procedia CIRP, volume = 122, pages = 73-78, year = 2024, note = 31st CIRP Conference on Life Cycle Engineering, issn = 2212-8271, doi = https://doi.org/10.1016/j.procir.2024.01.011, url = https://www.sciencedirect.com/science/article/pii/S2212827124000234, author = Heiner Reinhardt and Mahtab Mahdaviasl and Bastian Prell and Anton Mauersberger and Philipp Klimant and Jörg Reiff-Stephan and Steffen Ihlenfeldt, keywords = Identification, Knowledge management, Manufacturing system, Process control, Quality assurance, Sustainable development, Decision making, Complexity, Analysis, Design, abstract = Implementing processes for traceability is required in various industries to assure product quality during manufacturing, provide evidence on required processing conditions or facilitate product recalls. Commonly, radio-frequency identification (RFID) or code recognition techniques (e.g. Data Matrix) are applied to track the flow of workpieces through a manufacturing system and link processing data accordingly. Although the analysis of tracking data is well-examined, we still see a gap in the research on the trade-off between data acquisition, data analytics and data quality. Here, we present a framework to increase the value of existing data by enabling data analytics while addressing common pitfalls and reducing the costs of data management.</enrichment>
    <enrichment key="opus.import.dataHash">md5:fc1e1ab2150a8be29f1ed4a74b0804af</enrichment>
    <enrichment key="opus.import.date">2024-05-13T07:19:29+00:00</enrichment>
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    <enrichment key="opus.import.format">bibtex</enrichment>
    <enrichment key="opus.import.id">6641bf01916350.00042895</enrichment>
    <enrichment key="DOI_VoR">https://doi.org/10.1016/j.procir.2024.01.011</enrichment>
    <enrichment key="SourceTitle">Reinhardt, H., Mahdaviasl, M., Prell, B., Mauersberger, A., Klimant, P., Reiff-Stephan, J., &amp; Ihlenfeldt, S. (2024). Efficient data acquisition for traceability and analytics. Procedia CIRP, 122, 73–78. doi:10.1016/j.procir.2024.01.011</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
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    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0 International</licence>
    <author>Heiner Reinhardt</author>
    <author>Mahtab Mahdaviasl</author>
    <author>Bastian Prell</author>
    <author>Anton Mauersberger</author>
    <author>Philipp Klimant</author>
    <author>Jörg Reiff-Stephan</author>
    <author>Steffen Ihlenfeldt</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>identification</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>knowledge management</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>manufacturing system</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>process control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>quality assurance</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>sustainable development</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>decision making</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>complexity</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>design</value>
    </subject>
    <collection role="ddc" number="620">Ingenieurwissenschaften und zugeordnete Tätigkeiten</collection>
    <collection role="institutes" number="">Fachbereich Ingenieur- und Naturwissenschaften</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="green_open_access" number="1">Gold Open Access</collection>
    <thesisPublisher>Technische Hochschule Wildau</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-th-wildau/files/1923/1-s2.0-S2212827124000234-main.pdf</file>
  </doc>
  <doc>
    <id>2055</id>
    <completedYear>2025</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>526</pageFirst>
    <pageLast>531</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>134</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Objective validation for short-term material flow simulation</title>
    <abstract language="eng">Material flow simulation, by means of discrete event simulation (DES), is utilized in various industries to support production planning and control. This is due to the fact that changes to manufacturing systems and production strategies can be virtually examined before actual implementation. Since the manual development and repeated adjustment of simulation models is time-consuming and error-prone, numerous studies suggest computerized model generation and synchronization. However, validation of such generated or synchronized models is rarely considered. Here, we present an extendible objective validation technique for the repeated short-term simulation of a generated model. To illustrate this, the technique is applied to a high-volume automotive production line and a series of simulation cycles.</abstract>
    <parentTitle language="deu">Procedia CIRP</parentTitle>
    <identifier type="urn">urn:nbn:de:kobv:526-opus4-20554</identifier>
    <enrichment key="opus.import.date">2025-06-20T06:34:35+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">sword</enrichment>
    <enrichment key="DOI_VoR">https://doi.org/10.1016/j.procir.2025.02.170</enrichment>
    <enrichment key="SourceTitle">Reinhardt, H., Bogdanow, B., Arnold, R., Prell, B., Klimant, P., Seifert, F., Mahdaviasl, M. and Ihlenfeldt, S. (2025). Objective validation for short-term material flow simulation. Procedia CIRP, 134, 526–531. doi:10.1016/j.procir.2025.02.170</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Heiner Reinhardt</author>
    <author>Boran Bogdanow</author>
    <author>Roman Arnold</author>
    <author>Bastian Prell</author>
    <author>Philipp Klimant</author>
    <author>Frank Seifert</author>
    <author>Mahtab Mahdaviasl</author>
    <author>Steffen Ihlenfeldt</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>digital twin</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simulation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>quality</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>manufacturing system</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>analysis</value>
    </subject>
    <collection role="ddc" number="006">Spezielle Computerverfahren</collection>
    <collection role="ddc" number="670">Industrielle Fertigung</collection>
    <collection role="institutes" number="">Fachbereich Ingenieur- und Naturwissenschaften</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="Import" number="import">Import</collection>
    <thesisPublisher>Technische Hochschule Wildau</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-th-wildau/files/2055/1-s2.0-S2212827125005384-main.pdf</file>
  </doc>
  <doc>
    <id>2057</id>
    <completedYear>2025</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>562</pageFirst>
    <pageLast>566</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>134</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Subjective validation for short-term material flow simulation</title>
    <abstract language="eng">Material flow simulation, by means of discrete event simulation (DES), is frequently applied to support decision-making in production planning and control. However, manual modeling can be time-consuming and error-prone. Hence, numerous studies propose the automation of model generation and synchronization to overcome these challenges. However, in this context, validation techniques are rarely addressed. Therefore, we introduce a subjective validation technique for short-term material flow simulation based on a coherent methodology for data acquisition and visualization. The methodology is utilized to evaluate the outcome of an approach for computerized model generation and simulation. By means of an industrial use case, we hypothesize the causes for the deviation between the operation of a manufacturing system and the simulation of its generated virtual companion.</abstract>
    <parentTitle language="eng">Procedia CIRP</parentTitle>
    <identifier type="urn">urn:nbn:de:kobv:526-opus4-20576</identifier>
    <enrichment key="opus.import.date">2025-06-23T07:35:25+00:00</enrichment>
    <enrichment key="opus.source">sword</enrichment>
    <enrichment key="opus.import.user">sword</enrichment>
    <enrichment key="DOI_VoR">https://doi.org/10.1016/j.procir.2025.02.169</enrichment>
    <enrichment key="SourceTitle">Reinhardt, H., Bogdanow, B., Arnold, R., Prell, B., Klimant, P., Seifert, F., Mahdaviasl, M. and Ihlenfeldt, S. (2025). Subjective validation for short-term material flow simulation. Procedia CIRP, 134, 562–566. doi:10.1016/j.procir.2025.02.169</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Heiner Reinhardt</author>
    <author>Boran Bogdanow</author>
    <author>Roman Arnold</author>
    <author>Bastian Prell</author>
    <author>Philipp Klimant</author>
    <author>Frank Seifert</author>
    <author>Mahtab Mahdaviasl</author>
    <author>Steffen Ihlenfeldt</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>digital twin</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>simulation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>quality</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>manufacturing system</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>control</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>analysis</value>
    </subject>
    <collection role="ddc" number="003">Systeme</collection>
    <collection role="ddc" number="670">Industrielle Fertigung</collection>
    <collection role="institutes" number="">Fachbereich Ingenieur- und Naturwissenschaften</collection>
    <collection role="open_access" number="">open_access</collection>
    <collection role="Import" number="import">Import</collection>
    <thesisPublisher>Technische Hochschule Wildau</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-th-wildau/files/2057/1-s2.0-S221282712500544X-main.pdf</file>
  </doc>
</export-example>
