<p>Repair plays a pivotal role in the circular economy, but evaluating repairability factors such as disassembly times can be complex and time consuming. Existing tools listing proxy times to avoid such measurements had limited libraries of activities, only relevant to ICT product fasteners, and reassembly times were neglected or assumed to be equal to disassembly times, which is not always true. This study introduces the Disassembly and Reassembly Time (DaRT) model: a simplified, time-based tool developed from over 10,000 data points on many connection types from several household products, generating proxy times for many more activities applicable to many more product types. It also compared median times for disassembly and reassembly, showing which tasks are similar enough to use the same proxy time, while highlighting occasional differences, such as part-handling steps. Validated through comparisons with independent disassembly data for vacuum cleaners, washing machines, and smart TVs, DaRT demonstrates strong correlation and minimal bias. Balancing ease of use with reliability, it outperforms simpler step-count methods and offers greater practicality than the complex eDiM. Overall, DaRT enhances repair scoring systems, guides design for repair, and fosters a more circular electronics industry, ultimately fueling more sustainable innovation.</p>

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Modelling disassembly and reassembly times (DaRT) for assessing repairability

  • Sagar Dangal,
  • Linda Ritzen,
  • Alma van Oudheusden,
  • Jeremy Faludi,
  • Ruud Balkenende

摘要

Repair plays a pivotal role in the circular economy, but evaluating repairability factors such as disassembly times can be complex and time consuming. Existing tools listing proxy times to avoid such measurements had limited libraries of activities, only relevant to ICT product fasteners, and reassembly times were neglected or assumed to be equal to disassembly times, which is not always true. This study introduces the Disassembly and Reassembly Time (DaRT) model: a simplified, time-based tool developed from over 10,000 data points on many connection types from several household products, generating proxy times for many more activities applicable to many more product types. It also compared median times for disassembly and reassembly, showing which tasks are similar enough to use the same proxy time, while highlighting occasional differences, such as part-handling steps. Validated through comparisons with independent disassembly data for vacuum cleaners, washing machines, and smart TVs, DaRT demonstrates strong correlation and minimal bias. Balancing ease of use with reliability, it outperforms simpler step-count methods and offers greater practicality than the complex eDiM. Overall, DaRT enhances repair scoring systems, guides design for repair, and fosters a more circular electronics industry, ultimately fueling more sustainable innovation.