WIRLPOOL

Specialised in White Goods

Whirlpool Corporation is the biggest white goods business player in the world, with 60M products sold in 170 countries in 2018. Whirlpool EMEA is a relevant part of this business distributing around 20 Million appliances in a challenging business. In this context, it is crucial to provide:

  • the best features,

  • the widest functionalities range,

  • lower price,

  • the best quality.

The product conformity test is currently based on a statistical verification in a laboratory and is applied to pre-series or new variant products. The products are selected randomly and moved to dedicated labs which test the marketing key features.

This phase is mandatory to proceed to mass production, but it is generally not replicated during normal product lifecycle due to test duration and costs. It hinders the identification of eventual drifts in the manufacturing process. Covering the whole production lifecycle with the product conformity verification process would ensure a higher and more stable quality level for the final customers.

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Pilot partner

Technology Provider

Problem description

The main issue is the feasibility of a massive test execution on the whole production scope. The high duration of the test is not compliant with production pace and with the order to delivery timing of a just in time production, which is the current production planning model in Whirlpool factories. Currently, the tests are done before NPI (New Product Introduction) starts or, in a better case, along all the production lifetime but based on statistical samples.

 

The need to massively address all products implies the need to create advanced laboratory, with a considerable cost impact. The possibility to identify critical correlations between the nonconformity and some specific sets of data, may address a more focused action on testing campaign. These correlations could be used as alerts which may raise the level of warning on a specific product, being able to identify epidemic problems without applying conformity test to the whole production.

This possibility will lead surely to a higher efficiency in:

  • Problem detection,

  • Granting an early warning management,

  • Minimizing the costs related to laboratory empowerment in the factories’ environment.

To find all relevant correlations, it is necessary to extend as much as possible the scope of sources data sets, trying to include all the data that today are gathered:

  • at the shop floor (machines technical parameters, Statistical process Control data, EOL (End Of Life) Functional testing data),

  • in downstream processes (customer service calls data, customer network reviews),

  • data coming from a focused sensitisation (environmental data, etc.).

i4Q Solution

the use case will be conducted in the Dishwasher factory of Radomsko, Poland. An internal project is currently on-going to gather and provide cloud accessibility to data from different sources in the current production process:

  • assembly line,

  • production equipment,

  • functional test,

  • safety test,

  • aesthetics control,

  • rework.

All data from relevant sources will be used in a systematic and integrated way to infer conformity or non-conformity of each single product item produced.

i4Q services will be trained to correlate ongoing production data to prove conformity characteristics already known through earlier internal methods. i4Q tools will use this rich and deep dataset and specific business requirements to infer conformities and non-conformities in real time without an expensive and slow massive execution of tests.

i4Q will open a way to reuse available data to continuously estimate the current product’s quality, allowing the certification of product conformity at serial number level. Additionally, this continuous process verification can be used to detect drifts in the production’s quality.

Finally, the manufacturing line reconfiguration guidelines and the prescriptive analysis tools will allow adapting the manufacturing line to correct quality drifts before it compromises the conformity of several products.

Expected results

  • Reduction of expenses and capital by using a massive conformity test execution.

    • 50% reduction TCQ (Time -Cost-Quality) (from 120k€/factory to 60K€/factory)

 

  • Reduction of ramp-up time (production start-up) through a multi-step quality test methodology by correlating data sets and features of product conformity.

    • 15% reduction of ramp-up time (from 180 days to 150 days)

 

  • Increase of product quality through the early identification of drift in process quality allows to intervene on processes earlier than the time when issues arise and reducing the quantity of scrap produced.

    • 20% reduction of scrap, rework (from 8% to 6,4%)

 

  • Better product development lead by the knowledge by the correlation analysis, pushing to redesign process control levels and tolerances chain.

    • 10% decrease time to market (from 300 days to 270 days)