Whirlpool is opening a green field plant in Lodz/Poland. The white good that will be produced there is Dryer. Digitalizing the Factory, we want to reach a holistic approach to ZDM considering the full product lifecycle: from Product Design to Customer Service, cycling back to Product Design.
The pilot will leverage the outcomes of a previous research project (NMBP FP7 GRACE) and will integrate the QU4LITYdigital enablers and platforms (through the APIs) and the AQ control loops. The main innovation will be represented by the introduction in production of MPFQ model fused with AQ control loops: Functional Integration and Correlation between Material, Quality, Process and Appliance Functions.
The MPFQ-model is an acronym combined by the first characters of the four main elements:
- Material - as a collective term for everything that is needed to produce a certain product or product component. This may include raw materials, pre-products, consumables, operating supplies, product components and assemblies.
- Process - meaning production processes processing and transforming materials into the final goods by using machines, tools and human labour. This process is defined within the plant engineering.
- Function - meaning product feature and functions as distinguishing characteristics of a product item. This is mostly focused on functionalities as specific task, action or process the product is able to perform, but may also include other features like performance etc.
- Quality - measured as the degree of conformance of final product functions and features to customer requirements.
Every material, production process and product function/feature can be described by its technical characteristics and a collection of measured data. The processes can be additionally described as a sequence of process steps and their parameter setups. Product functions and features additionally contain performance indicators. These performance indicators may be evaluated by analysing and computing measured data from the materials forming this function, the process realizing the function or even by the directly measured data from the function measuring.
This innovative way to control quality and model data inherent to quality will be the fundamental approach that will lead to the vision of holistic Quality system.
In addition, it will be deployed AQ reference implementations to address unresolved problems in the vertical integration of data management (from data gathering to visualization and decision-making), enabling a holistic vision to be achieved.
The production process to build a Clothes Dryer comprises many stages; combination of automatic equipment and manual operation and all along the production process several Quality Stations are installed to perform gauge, to detect defective parts, filter them out or repair them. The main stages of the production process (Drum Line, Heat Pump, Side Fabrication, Main Assembly, Functional Test, ZHQ Area and Reliability Test) will be equipped with a Quality Gate, i.e. station to perform gauges and pass/fail test on product as well as Process monitoring means (OEE, SPC, Andon).
All these data sources will be integrated in the experiment, providing a comprehensive view of the production process.
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The end2end process supported by the overall architecture helps the operator and team leader in their daily activities in order to prevent and anticipate as much as possible quality issues on the product via the analysis of a huge amount of data linked together via the holistic semantic model.
The optimization of quality process decision is taking place thank to a holistic view of the factors that influence the perception of the quality from the consumer prespective. The platform using a MPFQ driven data model is enabling a faster, more reliable and flexible visualization system and analytical approach.
Part of the improved decision process enabled by the holistic platrom can be close looped into machine control parametes, allowing an autonomous quality management at factory level
Data are valorized thanks to a noevl data model based on MPFQ wich is correlating in a function based structured way components parmeters to process parameters to quality performances
Data are no more stored in silos but they can be used to represent the factors influencing a specifi behavior of process and product performances.
Data are no more stored in silos but they can be used to represent the factors influencing a specifi behavior of process and product performances.
Data architecture is based on a Industrial Ontology derived from MPFQ model
the use o a standard ontology is the basic mechanism to provide a semantic meaning to all the data generated af shopfloor level and enable a urther high degree o correlation with all the other company genarated data.
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The main innovation will be represented by the introduction in production of MPFQ model fused with AQ control loops: Functional Integration and Correlation between Material, Quality, Process and Appliance Functions.