Department of Business Development and Technology

Optimization of Packaging Processes for Special Orders Using Process Activity Mapping

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Packaging has a significant impact on the performance of logistic systems, therefore it is necessary to optimize the packaging process in order to enhance efficiency and add more value to a product and customer. This paper investigates the current packaging processes for special orders at one of stainless steel drainage systems manufacturers in Denmark. The aim of this research is to examine the packaging process for special orders and identify valuable and wasteful activities. The Process Activity Mapping has been selected to determine and eliminate waste. The analysis of the packaging process was carried out through direct non-participatory observations that listed 22 steps with recorded and calculated area, machine, distance moved, time spend, and people involved. Based on the analysis, only 5 out of 22 steps were identified as value-adding, 6 as necessary non-adding value and the rest as non-adding value. The majority of non-adding value and necessary non-adding value operations were related to transportation, waiting, inappropriate processing and unnecessary motion. Based on the results, the majority of wasteful activities was observed in the shrink wrapping station, where the propane torch is used to shrink the foil. Wrapping process requires highly intensive manual work that also triggers exceeded noise exposure and poor working postures. As a result, the research suggests a set of recommendations to establish a more optimized, efficient and ergonomic flow of packaging processes, including the rearrangement of activities, changes in the plant layout, and wrapping process automation.
Original languageEnglish
JournalProcedia Manufacturing
Number of pages10
Publication statusIn preparation - 9 Jun 2021

Bibliographical note

Jacob Søe Mikkelsen is MSc student at BTECH

    Research areas

  • Packaging, Process optimisation, process activity mapping, value-adding activities, Lean

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