BibTex Citation Data :
@article{J@TI82922, author = {Aura Mahabah and Yulizar Widiatama and Vina Yosephine}, title = {WASTE REDUCTION STRATEGY IN A SMALL-SCALE PACKAGING INDUSTRY USING THE WASTE ASSESSMENT MODEL AND PROCESS ACTIVITY MAPPING: A TIME-BASED DIAGNOSTIC APPROACH}, journal = {J@ti Undip: Jurnal Teknik Industri}, volume = {21}, number = {3}, year = {2026}, keywords = {Lean Manufacturing; Process Activity Mapping; Small and Medium Enterprises; Packaging Industry; Waste Assessment Model}, abstract = { Small and medium enterprises play a crucial role in manufacturing-based economies but frequently experience operational inefficiencies caused by unmanaged production waste. Unlike large firms, SMEs often operate with manual processes, limited standardization, and restricted data availability, making systematic waste analysis challenging. This study aims to identify the dominant waste drivers and their interrelationships through a case study of a small-scale packaging manufacturing enterprise using a lean manufacturing approach. The study integrates the Waste Assessment Model (WAM) and Process Activity Mapping (PAM) to evaluate waste behavior in the packaging headgear production process. Data were collected through direct observation, time-study measurements, and structured interviews with the enterprise owner. PAM was used to classify activities as value-added (VA), necessary non-value-added (NNVA), or non-value-added (NVA), while WAM was used to quantify the interrelationships among waste categories through a Waste Relationship Matrix (WRM). The results indicate that approximately 40% of total production time consists of NNVA and NVA activities. Overproduction (21.50%), motion (19.63%), and overprocessing (14.02%) were identified as the dominant root wastes, whereas waiting (17.76%) and inventory (16.82%) were the most affected waste categories. The findings demonstrate that waste in small-scale manufacturing systems is structurally interconnected. The integration of WAM and PAM provides a low-resource diagnostic framework to support practical waste reduction strategies in SMEs. }, issn = {2502-1516}, pages = {290--299} doi = {10.14710/jati.21.3.290-299}, url = {https://ejournal.undip.ac.id/index.php/jgti/article/view/82922} }
Refworks Citation Data :
Small and medium enterprises play a crucial role in manufacturing-based economies but frequently experience operational inefficiencies caused by unmanaged production waste. Unlike large firms, SMEs often operate with manual processes, limited standardization, and restricted data availability, making systematic waste analysis challenging. This study aims to identify the dominant waste drivers and their interrelationships through a case study of a small-scale packaging manufacturing enterprise using a lean manufacturing approach. The study integrates the Waste Assessment Model (WAM) and Process Activity Mapping (PAM) to evaluate waste behavior in the packaging headgear production process. Data were collected through direct observation, time-study measurements, and structured interviews with the enterprise owner. PAM was used to classify activities as value-added (VA), necessary non-value-added (NNVA), or non-value-added (NVA), while WAM was used to quantify the interrelationships among waste categories through a Waste Relationship Matrix (WRM). The results indicate that approximately 40% of total production time consists of NNVA and NVA activities. Overproduction (21.50%), motion (19.63%), and overprocessing (14.02%) were identified as the dominant root wastes, whereas waiting (17.76%) and inventory (16.82%) were the most affected waste categories. The findings demonstrate that waste in small-scale manufacturing systems is structurally interconnected. The integration of WAM and PAM provides a low-resource diagnostic framework to support practical waste reduction strategies in SMEs.
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