This study demonstrates application of Lean techniques to improve working process in

a sewing machine factory, focusing on the raw material picking process. The value stream

mapping and flow process chart techniques were utilized to identify the value added activities,

non-value activities and necessary but non-value added activities in the current

process. The ECRS (Eliminate, Combine, Rearrange and Simplify) in waste reduction was

subsequently applied to improve the working process by (i) adjusting the raw material picking

procedures and pre-packing raw material as per demand, (ii) adding symbols onto the

containers to reduce time spent in picking material based on visual control principle, and

(iii) developing and zoning storage area, identifying level location for each row and also

applying algorithms generated from a solver program and linear programming to appropriately

define the location of raw material storage. Improvement in the raw material picking

process was realized, cutting down six out of 11 procedures in material picking or by 55%,

reducing material picking time from 24 to 4 min or by 83%. The distance to handle material

in the warehouse can be shortened by 120 m per time or 2,400 m per day, equal to 86%

reduction. Lean techniques

The implementation of milk-run in Indonesia has been started since 2005. As a developing

country, there is a challenge to operate milk-run smoothly especially in urban area due to

severe traffic congestion and unfavourable road condition in some areas. This research aimed

to analyze the practice of milk-run operation in one of the biggest Japanese automotive

companies in Indonesia. Transportation Value Stream Mapping (TVSM) is applied in order

to perform just-in-time delivery in the supply chain before operating milk-run. It is discussed

that this company still need to continue in improving milk-run operation. The operation

system needs control and integration from manufacturer, supplier and logistics partner.

The advantage of milk-run operation is cost reduction and also support green logistics in

decreasing emission of carbondioxide (CO2) by reducing the number of trucks used.