Case Studies

Based on the Analysis, element selected that was detrimental to the high Maintenance Cost were the following:

• No Price by location
• Outsourcing of work
• PO value < RM 3000
• PO value < RM 500

Therefore, during the Improvement, the elements above were improved in stages and gained the Control by using a maintenance cost monitoring plan.

Case Studies 2: “ Reduction Of Energy Consumption On Electricity And Natural Gas”

Our client basically had high cost on Energy Consumption for Electricity And Natural Gas. Based on data, the increase was incremental year to year basis. The usage for year 2007:

• Electricity is 10,138,670 kWh
• Natural Gas is 1,614,528 M³

During Measure Stage the Green Belt candidate found out potential factors affecting the project using various kinds of tools as follow :

• Process Mapping
• Supplier, Input, Process, Output, Customers (SIPOC)
• Cause & Effect
• Failure Mode and Effects Analysis

Based on the Analysis, element selected that were detrimental to the high energy consumption were the following:

• No machine tuning after total service (Chiller / Boiler)
• No local spare part stock
• No inverter installed
• Outdated technology / machine ageing
• No preventive checking / monitoring mechanism

Case Study 3: “Minimizing Material Loss”

One of our client studied data that showed some plants have materials losses higher than current goal (KPI). The calculated financial impacts to company for above losses are RM2.20 per m3 at the plants in total.

For Define phase the following were completed:

• Material Gain/Loss Trend Analysis including value
• SIPOC Charts
• Material Receiving Process Map
• Material Batching Process Map
• VOC Data

For the Analyse Phase, the following were completed:

• Pareto Chart to identify key problem areas for material loss
• FMEA for Action Plan

From analysis, the following were found to be detrimental to material loss:

• High Moisture in Material
• Inefficient stockpile preparation
• Non weighing check completed
• Bad equipment condition and repair status

For the Measure phase, the following were completed:

• Cause and Effect Diagram for Material Loss at Receiving, Stockpile and Batching.
• Data Collection Plan and Sheet
• Z Bench (average sigma value at -0.51)
• FMEA for each Process Stage for Material Loss

For Improve and Control Stage, the following actions were taken:

• Monitoring of moisture, stockpile and equipment condition
• Construct concrete based stockpile
• Construct pit weighbridge
• Throughput purchase
• Sourcing from another supplier
• Improved drainage systems
• Replacement of sand with cheaper alternatives
• Coaching of plant heads and monitoring plant performaces

Case Study 4: “Increase High Value Quarry Production”

One of our client found that the existing plant design produced c/run (low value product) about 58% from total production tonnage since 1993. Management has decided to produce more of 20 mm aggregate, 10 mm chipping and quarry dust (high value products) up to 70% of total production. The existing plant flow is unable to fulfill the management request.

For Define phase the following were completed:

• Selling Price of high and low value product Trend Analysis
• SIPOC Charts
• Quarry Product Processing Process Map
• VOC Data

For the Measure phase, the following were completed:

• Cause and Effect Diagram for Insufficient production of high value products.
• Data Collection Plan and Sheet
• Z Bench (average sigma value at -2.08)
• FMEA for each Process Stage for Quarry Processing

For the Analyse Phase, the following were completed:

• Pareto Chart to identify key problem areas
• FMEA for Action Plan

From analysis, the following were found to be detrimental to material loss:

• Plant Design
• Demand from Customers
• Plant Breakdowns

Therefore, in Improve and Control Phase, the following were implemented:

• Modify plant design
• Revise pricing for c/run products
• Train plant workers on new plant flow system
• Inform and Agree with Sales department on monthly production plan

Case Study 5: “Improving the Linen & Laundry Services for Hospital”

One of our client studied data that showed most Linen weight per bed is not fulfill as it targeted as below

• Actual Receive : 4.85 kg/Bed
• Target : 5.34 kg/Bed

For Define phase the following were completed:

• Linen Shortfall Trend Analysis including value
• SIPOC Charts
• Laundry Plant Process Map
• In-house Linen Process Map
• VOC Data

For the Measure phase, the following were completed:

• Cause and Effect Diagram for Linen Shortfall
• Data Collection Plan and Sheet
• Z Bench (average sigma value at -1.09)
• FMEA for each Process Stage for Supplier & In-house Linen

For the Analyze Phase, the following were completed:

• Pareto Chart to identify key problem areas
• Statistical tools (2 sample T- Test, regression analyze) were used to determine vital X’s factor.
• FMEA for Action Plan

Therefore, in Improve and Control Phase, the following were implemented:

• Revise process flow for In-house linen
• Train In-house workers for new process flow for linen
• Launch Linen loss prevention program
• Review Agreement with Supplier Linen term of delivery.
• Replicate the improvement to other area.