Identifikasi Waste pada Produksi Kayu Lapis dengan Pendekatan Lean Manufacturing untuk Meningkatkan Kualitas Proses Produksi (Studi Kasus : PT Sumber Mas Indah Plywood)
Abstract
This research aimed at identifying the wastes of plywood production in PT Sumber Mas
Indah Plywood. Results were then utilized to determine methods in reducing wastes. The
identification of waste was carried out using lean manufacturing approach. The data were
collected from manufacturer records, study to determine processing time, as well as interview
and quisioners which were distributed to workers in each department. Big picture mapping and
value stream mapping tools (VALSAT) were then utilized to process the data. Results of
analyses using big picture mapping showed that total production lead time was 438,8 minutes,
with 235,97 minutes of them were value added activities; and 27 days of total information lead
time. Workshop waste analyses resulted in the highest waste generated during plywood
production process. Those were 133 waiting time (delay), 113 defect and 78 excessive
transportation. Further analyses using VALSAT showed three methods to identify the data in
more detail, namely process activity mapping (PAM), supply chain response matrix (SCRM)
and quality filter mapping (QFM). Results from PAM method revealed 125 activities during
production, consist 62 value added activities, 33 necessary but non value added activities and 30
non value added activities. While results from SCRM showed the average 22,63 days of total
order fulfillment process comprised of 4,13 days of total physical stock and 18,5 days of total
lead time. QFM result showed ratio of scrap defect reject 0,4% and ratio of scrap defect UTY
3,46%. In general waste in plywood production at PT Sumber Mas Indah Plywood was
generated from worker, material, machinery, methods and environment. One of the ways to
improve it is by applying pull system (Kanban)Keywords
Full Text:
PDF (Bahasa Indonesia)DOI
https://doi.org/10.21107/agrointek.v4i1.2739Metrics
Refbacks
- There are currently no refbacks.
Copyright (c) 2017 AGROINTEK
This work is licensed under a Creative Commons Attribution 4.0 International License.