LEARNING LAUNCH TOOL

Elimination of Vehicle Field Failures

Challenge

I am working in product development team for design and development of defense vehicles. These

vehicles are designed and manufactured keeping in mind the stringent and challenging conditions armed

forces have to operate in. We have supplied 255 numbers of 8x8 vehicles to Indian Army used for

carrying ammunition and other logistic services. The vehicles are in service and operating in different

parts of northern India for past one year. Recently, we got few cases of tire burst in some of these field

vehicles. This is a safety critical issue which had to be resolved at the earliest for smooth operation of

these vehicles and to avoid such failures in the future.

Selection

This was the case where our team had to find out the root cause of these failures and to provide a

permanent solution for the same. But before implementation of the solution in all 255 numbers of field

vehicles, we had to be sure of what we are proposing will be effective and will put an end to these

failures. And what better way to test our solution then learning launch tool. We used this tool to test

our assumptions and analysis of the problem.

Application

We did two pilot runs to arrive at a solution to the problem which can be implemented in the field

vehicles. We formed a cross functional team for root cause analysis of the problem which included

members from design, quality, manufacturing and service teams and also members from tire supplying

firm. This vehicle was equipped with Central Tire Inflation System (CTIS) which helps in maintaining and

changing the tire pressure from the cabin itself based on the vehicle payload and operating terrain. After

analysis of the vehicles in which tire burst cases were seen, our team identified running of vehicles with

under pressurized tires was the root cause and one of the CTIS braided hose which was supplying the air

to tires from the compressor was having leakage issue. For our first pilot run we modified the design of

the braided hose where we used the improved material for the O ring which was getting damaged under

extreme heat conditions and resulting in leakage from the joint. We ordered eight numbers of these

improved braided hoses for trial at our technical center proving grounds. The vehicle was fitted with

these improved hoses and was taken for highway trials. After completing four thousand kilometers we

found that O rings got damaged and resulted in air leakage from the front interface of the braided hose.

For our second pilot run, we redesigned our braided hose and this time we eliminated O ring itself from

the design and modified hose interface in such a way that it didn’t require O ring for sealing of the joint.

We ordered these improved hoses again for fitment trial in the vehicle and again performed the

highway trials. This time we didn’t find leakage at any point of time during trial duration.

Insight

The use of learning launch tool gave us assurance that, the solution we identified were effective in

arresting the air leakage from the tires and one, which can be implemented in the field vehicles to avoid

any further failures. Also it showed us the assumptions made during first design modification were not

correct, which we got it correct during our second modification. If we had gone directly for field

implementation without any learning launch, then we would have failed miserably and this would have

resulted in wastage of money and time along with damage to firm’s reputation. We successfully

implemented the second design in the field and eliminated the air leakage issue in vehicles which was

giving rise to tire burst cases.

Approach

The experience gained from the two learning launches were very insightful and seeing the effectiveness

of the solution we horizontally deployed this design modification in other vehicle platforms like 6x6,

10x10 and 12x12 where the Central Tire Inflation System is being used. Also we understood the

importance of a pilot run of any new design concept before taking it for large scale implementation. This

is very much required to reduce the chances of failure and also the wastage of resources.

