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Short-run statistical process control, often referred to as nominals, target or DNOM charting or Z charting, is perceived as the solution for manufactures with a high mix- low volume environment. In this article we will show it should be used in a lot more environments and we also show how this can be easily realized with DataLyzer Qualis 4.0. |
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This white paper shows how you can really implement a working quality system where the techniques come together. |
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This white paper explains how you can combine SPC and SQC in an organization to get the best of both worlds. |
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Integrating SPC and OEE in one improvement approach and using an integrated software solution has advantages:
– Productivity and quality will be equally important, and the company will truly benefit if both are improved.
– The methodology for continuous improvement will be accepted faster when both methods are integrated- and supported by one approach and an integrated software solution.
– When companies use both methods, time required for training, system support and system maintenance is reduced.
This white paper explains the differences between the techniques and shows the advantages of integrating the continuous improvement methods. |
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This white paper shows how statistical process control should be applied in combination with big data. |
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There is a lot of confusion about the use of Cp, Cpk, Pp, and Ppk. This white paper tries to remove some of the confusion and shows the power of using the indices Cp, Cpk, and Ppk simultaneously. |
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This white paper shows how DataLyzer can support with the implementation of an effective and efficient APQP process. |
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This white paper describes how to set control limits during the implementation of SPC to make sure the organization can handle the number of out of controls. |
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This white paper recommends the use of two new indices to allow a quick and effective comparison between limits set historically and the current process. |
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This white paper shows how SPC (Control Charts) can be used as a tool to support process improvement. |
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During SPC implementation, often too much emphasis is put on the use of the Average chart. This white paper explains mistakes made in this area and gives recommendations on how to prevent these mistakes. |
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This white paper describes which issues are important when you implement SPC in processes where you have parallel subprocesses like multiple cavities, multiple lanes, etc. |
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In this white paper, it is explained how you can implement full tracking and tracing and how you can use DataLyzer to quickly analyze causes of variation. |
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In this white paper, we show how advanced analysis can be used to analyze data gathered by DataLyzer. |
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In this white paper, we show how a CMM can be integrated into the SPC DataLyzer network. |
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In this white paper, we shed some light how the Zero Defects approach is used more and more in the Aerospace supply chain and how DataLyzer can support with this implementation
The Aerospace industry is rapidly adopting a Zero Defects approach throughout its supply chain.
Achieving Zero Defects cannot be done successfully with current quality systems. New approaches, like those developed in automotive and semiconductor manufacturing will need to be adopted. |
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More and more companies are looking for an SPC software tool which fits in their Industry 4.0 approach. This whitepaper describes the criteria to take into account, when you are looking for an SPC software solution |
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In this whitepaper we show how Big data, OEE and SPC are seamlessly integrated in DataLyzer. |
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In this whitepaper we show the challenges with automatic import of data into an SPC software solution and these challenges are solved in DataLyzer. |
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In real-time SPC systems we see more and more automated import. For example CMM data, PLC data, camera data. To get maximum results from your SPC implementation it is critical you keep your operators involved.
In this whitepaper we show how you can keep operators involved when data is completely imported automatically. |
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In this whitepaper we show that applying SPC in modern industry requires a different approach how to set control limits. 3 sigma limits should not be applied in most situations |
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Artificial Intelligence and Machine Learning (Further abbreviated as AI) are buzzwords that are raising a lot of interest in manufacturing.
Applying AI is not easy and should not be taken lightly. In this whitepaper, we will explain how you can take the first steps in AI and what the prerequisites to applying AI are.
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This white paper aims to provide an overview into the Cost of Quality and to discuss ways to control the cost of quality.
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SPC in Crystalline PV module manufacturing
In this white paper, we explain how you can benefit from implementing DataLyzer Spectrum. Please send us a mail if you like to receive this white paper. |
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