Benchmarks & Client Cases

Pull Flow Model in Discrete Assembly

The Challenge

pusl model
functional layout


• Finished goods inventory coverage of 15 days with a customer service level of 93% - dysfunctional inventory

• Raw materials and parts stock coverage of 30 days

• Between 1 and 5 days of WIP in production and assembly lines

• 50% of planned production lost due to lack of parts and poor line efficiency

Root Causes

• Finished goods planning based on order forecasts: forecast errors between -18% and 16%

• Functional layout: preassembly lines separated from final assembly lines

• Operators isolated from each other, parts returned to the warehouse, supply of large pallet-sized containers, poor operator standard work, low line balancing efficiency

• Delivery to final assembly line by forklifts, under the instruction of operators or supervisors

The Solution

pull model

line design border of line flow cell leayout

• Pull planning algorithm used on a daily basis to compare a certain replenishment level with the current stock of finished goods and create the production orders according to deviations

• Transformation of orders into KANBAN and planning on a daily basis through a logistics box

• Daily schedule determined by freezing one day of production according to levelling rules

• Transformation of one assembly line to two with fewer product references on each; zero changeover time; balanced operation time between operators; small containers on the border of line

• Three Mizusumashi circuits for purchased parts, sub-assemblies and finished goods

The Results

The project had a Payback period of 5 months with annual savings surpassing £3 million.

Internal Defects

Internal Defects

Number of rejected parts reduced by 52% (measured in parts per million)



Number of parts produced by each operator increased by 36% (on average)

Inventory Coverage

Inventory Coverage

Finished goods stock coverage reduced from 50 days to 30


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