Pengembangan Extended Value Stream Mapping Untuk Identifikasi Eight Muda Wastes

Sahdhani, Muhammad Arkan (2025) Pengembangan Extended Value Stream Mapping Untuk Identifikasi Eight Muda Wastes. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Value Stream Mapping (VSM) merupakan salah satu alat dalam Lean Manufacturing untuk memetakan aliran nilai dan mengidentifikasi pemborosan. Namun, VSM Tradisional masih memiliki keterbatasan dalam mengidentifikasi waste secara menyeluruh dan tidak mempertimbangkan aspek faktor manusia dan lingkungan kerja. Extended VSM yang dikembangkan dalam penelitian ini memperkenalkan peta aliran nilai yang lebih komprehensif dalam mengidentifikasi delapan jenis Muda Wastes. Pengembangannya didasarkan pada tiga aspek utama, yaitu aspek manufaktur dari VSM Tradisional, aspek ergonomi dari Ergo-VSM, dan aspek lingkungan dari Environment-VSM. Keterlibatan aspek-aspek tersebut juga tidak terlepas dari tools lainnya, seperti Stopwatch Time Study, REBA, dan NASA-TLX, untuk membantu mengidentifikasi pemborosan akibat kondisi lingkungan kerja dan postur kerja yang tidak ergonomis, beban mental, dan non-utilized talent. Selain itu, juga dilakukan penentuan visualisasi yang didasarkan pada tools pemetaan lainnya, seperti Sankey Diagram, Ergo-VSM, Cost-based VSM, dan Service-VSM. Studi kasus dilakukan di PT Barata Indonesia pada Foundry I – proses produksi komponen Bogie S100FN. Hasil pengukuran menunjukkan bahwa pada operasi Setup Core terdapat waste motion dan non-utilized talent yang tinggi. Waste motion ditunjukkan melalui skor REBA senilai 9 yang diakibatkan oleh tingginya frekuensi aktivitas menjangkau secara berulang dan aktivitas membungkuk. Sementara itu, waste non-utilized talent ditunjukkan melalui skor NASA-TLX yang mencapai 75. Selain itu, pengukuran pencahayaan menunjukkan nilai di bawah standar minimal 250 lx, yang berpotensi mengurangi visibilitas dan menimbulkan waiting time saat pengerjaan. Visualisasi temuan-temuan tersebut ditunjukkan melalui blok informasi, kode informasi waste, dan action level dalam Extended VSM, yang memungkinkan identifikasi area pemborosan terperinci. Framework Extended VSM telah divalidasi oleh para pakar industri terbukti lebih efektif dalam menemukan hidden waste, terutama yang berasal dari faktor manusia dan operasional.
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Value Stream Mapping (VSM) is a widely used tool in Lean Manufacturing for mappingthe flow of value and identifying waste. However, the traditional VSM exhibits several limitations in identifying waste comprehensively and it often overlooks human factors and environmental conditions. The Extended VSM proposed in this research enables a more comprehensive value stream map in identifying the eight types of Muda Wastes. Its development integrates three main aspects: the manufacturing aspect of traditional VSM, the ergonomics aspect of Ergo-VSM, and the environmental aspect of Environment-VSM. The involvement of these aspects is also complemented by other tools, such as Stopwatch Time Study, REBA, and NASA-TLX, to help identify waste due to poor environmental conditions, non-ergonomic postures, mental workload, and non-utilized talent. To enhance the visualization and interpretation, Extended VSM also incorporates mapping tools, such as Sankey Diagram, Ergo-VSM, Cost-based VSM, and Service-VSM. This framework was applied in a case study at PT Barata Indonesia in Foundry I – the production process of Bogie S100FN components. Findings from the Core Setup operation revealed high motion waste and non-utilized talent. Motion waste is indicated by a REBA score of 9, reflecting high repetition in reaching and bending activities. Meanwhile, non-utilized talent waste is indicated by a NASA-TLX score of 75, pointing to a high mental load. Additionally, lighting measurements were recorded below the recommended 250 lx standard, suggesting potential impacts on visibility and increased waiting time. These findings were visualized using information blocks, waste information codes, and action levels in the Extended VSM, providing a detailed overview of waste identification areas. This framework has been validated by industry experts, shown to be more effective in identifying hidden waste, especially those linked from human and operational factors.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Eight Muda Wastes, Environmental Condition, Extended VSM, Hidden Waste, Ergonomics, Value Stream Mapping
Subjects:	T Technology > TS Manufactures > TS183 Manufacturing processes. Lean manufacturing.
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26101-(S2) Master Thesis
Depositing User:	Muhammad Arkan Sahdhani
Date Deposited:	04 Aug 2025 06:26
Last Modified:	04 Aug 2025 06:26
URI:	http://repository.its.ac.id/id/eprint/125668

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