View in EDS HTML Full Text PDF Full Text

Simulating operator learning during production ramp-up in parallel vs. serial flow production.

Saved in:
Bibliographic Details
Title: Simulating operator learning during production ramp-up in parallel vs. serial flow production.
Authors: Neumann, W. Patrick1 (AUTHOR) pneumann@ryerson.ca, Medbo, Per2 (AUTHOR)
Source: International Journal of Production Research. Feb2017, Vol. 55 Issue 3, p845-857. 13p.
Subjects: Ergonomics, Discrete element method, Product usage segmentation, Human factors in management information systems, Production (Economic theory), Product life cycle
Abstract: The aim of this research is to demonstrate how human learning models can be integrated into discrete event simulation to examine ramp-up time differences between serial and parallel flow production strategies. The experimental model examined three levels of learning rate and minimum cycle times. Results show that while the parallel flow system had longer ramp-up times than serial flow systems, they also had higher maximum throughput capacity. As a result, the parallel flow system frequently outperformed lines within the first weeks of operation. There is a critical lack of empirical evidence or methods that would allow designers to accurately determine what the critical learning paramters might be in their specific operations, and further research is needed to create predictive tools in this important area. [ABSTRACT FROM PUBLISHER]
Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 120156599
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Simulating operator learning during production ramp-up in parallel vs. serial flow production.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Neumann%2C+W%2E+Patrick%22">Neumann, W. Patrick</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> pneumann@ryerson.ca</i><br /><searchLink fieldCode="AR" term="%22Medbo%2C+Per%22">Medbo, Per</searchLink><relatesTo>2</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Production+Research%22">International Journal of Production Research</searchLink>. Feb2017, Vol. 55 Issue 3, p845-857. 13p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Ergonomics%22">Ergonomics</searchLink><br /><searchLink fieldCode="DE" term="%22Discrete+element+method%22">Discrete element method</searchLink><br /><searchLink fieldCode="DE" term="%22Product+usage+segmentation%22">Product usage segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Human+factors+in+management+information+systems%22">Human factors in management information systems</searchLink><br /><searchLink fieldCode="DE" term="%22Production+%28Economic+theory%29%22">Production (Economic theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Product+life+cycle%22">Product life cycle</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The aim of this research is to demonstrate how human learning models can be integrated into discrete event simulation to examine ramp-up time differences between serial and parallel flow production strategies. The experimental model examined three levels of learning rate and minimum cycle times. Results show that while the parallel flow system had longer ramp-up times than serial flow systems, they also had higher maximum throughput capacity. As a result, the parallel flow system frequently outperformed lines within the first weeks of operation. There is a critical lack of empirical evidence or methods that would allow designers to accurately determine what the critical learning paramters might be in their specific operations, and further research is needed to create predictive tools in this important area. [ABSTRACT FROM PUBLISHER]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Production Research is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=120156599
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/00207543.2016.1217362
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 845
    Subjects:
      – SubjectFull: Ergonomics
        Type: general
      – SubjectFull: Discrete element method
        Type: general
      – SubjectFull: Product usage segmentation
        Type: general
      – SubjectFull: Human factors in management information systems
        Type: general
      – SubjectFull: Production (Economic theory)
        Type: general
      – SubjectFull: Product life cycle
        Type: general
    Titles:
      – TitleFull: Simulating operator learning during production ramp-up in parallel vs. serial flow production.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Neumann, W. Patrick
      – PersonEntity:
          Name:
            NameFull: Medbo, Per
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 02
              Text: Feb2017
              Type: published
              Y: 2017
          Identifiers:
            – Type: issn-print
              Value: 00207543
          Numbering:
            – Type: volume
              Value: 55
            – Type: issue
              Value: 3
          Titles:
            – TitleFull: International Journal of Production Research
              Type: main
ResultId 1