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Datalyzer Qualis Analytics Software

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DataLyzer SPC Wizard Software

The movie below gives you a quick introduction in the functionality of the SPC Wizard software.

Example training session with SPC Wizard

SPC Wizard has 10 lessions for self training. The movie below shows an example of a self paced training about process capability.

Qualis Analytics Overview

In Q1 2026 DataLyzer will release webbased Qualis Analytics. This will be an advanced analysis tool with full Lean Six Sigma analysis capabilities and Machine learning. It can work completely integrated with other DataLyzer tools but also can be used stand-alone in a Lean Six Sigma implementation. Reach out for more inforamtion.

Understanding the concepts of SPC at every level in the organization is very crucial to a successful implementation of SPC. After successful implementation, the right interpretation of the statistics determines next steps in the continuous improvement process. For a quality manager, having access to statistical tools is essential. Quick access to the quality data helps engineers focus on problems rather than switching across tools.

Qualis Analytics is the tool that meets these critical requirements. Qualis Analytics seamlessly integrates with all other tools in the Qualis suite but also to any other data source like databases or Excel, thereby offering very easy access to online data for analysis.

 

Benefits

  • Advanced analysis tools in webbased application.
  • All users work in their own workspaces.
  • Option to combine data from multiple sources without the need to import.
  • Integrates with the realtime DataLyzer SPC database
  • Machine learning tools like Decision Tree Analysis and Ngrams
  • Hypothesis testing; Mean test, Median tests, Variance tests and Proportion tests available.
For more details, please see our brochure.

Flexible and Agile Usability of common Data Analysis Tools

Provides facility to easily select any section of the data, include/exclude data points with any combination of attributes, with instantaneous creation/refresh of control charts, histograms, Pareto’s, scattergrams, multi-vari and F and T-test allowing the needed flexibility  during analysis. This makes Qualis Analytics an excellent tool in your Six Sigma implementation or for promoting the use of SPC with suppliers.

Quick Import

Data can be imported real-time from the DataLyzer SPC database, Microsoft Excel and other SQL Server databases with or without previous setup. In Excel it is possible to define the SPC setup so automatically all chart settings are available when data is imported from Excel.

Control Chart Analysis

Control chart can be created and analysed. Qualis Analytics contains calculated control limits using any section of the data with multiple calculation rules;

  • make analysis based on parameters added to the chart like operators, order numbers, article numbers etc.
  • select attributes to appear in a chart;
  • multiple control charts in one screen;
  • time based analysis;
  • review user notes from samples;
  • exclude points from the calculations

Capability Analysis

Qualis Analytics can create histograms against a given set of data and allow several following options to aid investigation, for example:

  • Toggle between real standard deviation and estimated standard deviation
  • Dragging of Specification Limits (temporary) which useful for investigating process capability.
  • Scales are made identical while studying multiple histograms

Correlation Analysis

Correlation can be made between variable data, attribute data and numeric optional parameters. A full correlation heatmap table can be created between multiple columns in the data set. During analysis data points can be excluded in the Scattergram view.

Pareto Analysis

Pareto graphs can be made from attribute data but also from logbook entries. Specific columns can be excluded from the analysis.

Multi Vari Analysis

Multi  Vari analysis based on time and parameters (operators, suppliers and  machines etc) up to three factors, serving as a preliminary tool to get ideas for further investigation.  Qualis Analytics provides a feature to pick the response data points to instantly conduct the F- & T-test  in steps showing the normal curve, confidence interval and the data itself.

Frequency Analysis

Qualis Analytics allows instantaneous frequency analysis of events with grouped and ungrouped data against time and parameters with Pareto ordering and percentage.

Advanced Data Set Operations

In addition to the common tools, Qualis Analytics contains some advanced tools to analyze data. You can for example combine data from different data sources and join the data based on a common parameter (e.g. Serial number) or based on matching date and time values or time differences. Multiple data sources can be combined automatically.

Machine Learning

Machine learning Decision Tree Analysis (Random Forest) is implemented in Qualis Analytics. In many manufacturing processes interaction between quality inputs collectively impact outcomes of CTQs. With predictive outcome analysis using Decision Trees, we can make a model of these data streams including all interactions and show the predicted quality of the CTQs.  For textual data, we have implemented Ngrams analysis. More Advanced tools will be added as per customer requests.

Hypothesis Testing

For hypothesis testing, we support several Inferential Statistics like Mean Tests, Median Tests, Variance Tests and Proportion Tests. The Mean Tests include the 1 sample t-test, 2 sample t-test and One way ANOVA tests. Median Tests include the Sign Test, Mann-Whitney Test and the Kruskal-Wallis Test. The Variance Tests include 1 sample variance-test, the F-test and the Bartlett Levene test. Proportion tests include the 1 sample proportion-test, the 2 sample proportion-test and the Chi square test.

For all tests it is possible to adjust the Confidence levels and define the Alternative Hypothesis.

How to integrate FMEA, Control Planning, SPC and CAPA

This white paper shows how you can really implement a working quality system where the techniques come together.

SPC and SQC integrated

This white paper explains how you can combine SPC and SQC in an organization to get the best of both worlds.

Integrating SPC and TPM

This white paper shows how you can integrate the two continuous improvement methods.

APQP: Ballooning Control Plan SPC

This white paper shows how you can integrate the design results with the quality planning and the quality execution process.

Process Capability Indices

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.

Managing Control Limits

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.

Recalculating the Control Limits

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.

Using Control Charts for Quality Improvement

This white paper shows how SPC (Control Charts) can be used as a tool to support process improvement.

Importance of the Range Chart

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.

Parallel Processes and SPC

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.

Tracking and Tracing

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.

Reject reduction by analysis of process data

In this white paper, we show how advanced analysis can be used to analyze data gathered by DataLyzer.

CMM Data acquisition and Chart creation

In this white paper, we show how a CMM can be integrated into the SPC DataLyzer network.

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.