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DataLyzer
SPC Wizard 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.

SPC Wizard Overview

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.

SPC Wizard is the tool that meets these critical requirements. It is unique in the industry because it combines a complete SPC training module containing lessons, process simulations and a process improvement game with full functionality for real-time data entry and advanced analysis of both variables and attributes. SPC Wizard seamlessly integrates with the DataLyzer Spectrum database, thereby offering very easy access to online data for analysis.

Benefits

  • Effective training on SPC concepts.
  • Highly interactive, simulation-based game, making learning fun.
  • Advanced analysis tools.
  • Option to combine data from multiple sources without the need to import.
To more details, please see our brochure.
Self-paced Step-by-Step Tutorials

The Tutorials contain an explanation of SPC concepts in simple English with a guide to use the simulators, encouraging a hands-on approach in learning concepts. Dr. Deming’s Experiments SPC Wizard contains simulations of Dr. Deming’s Red Beads Experiment and Funnel Experiment showing how easy it is to come to the wrong conclusions about people and processes by looking at just raw data. This is a must.

Process Simulations

DataLyzer’s own Tennis Ball Launcher and Bead box simulation programs generate ‘variable’ and ‘attribute’ type data that is required to recreate scenarios: Eg To produce data that shows special cause of variation.

Process Improvement Game

The game simulates a process that is not initially in a state of statistical control. The student has to apply the SPC techniques to improve the process. The game is won when a required capability is achieved.

Flexible and Agile Usability of common SPC Tools

Provides facility to drag and drop data, 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 and Scattergrams.

Quick Import

Data can be analyzed on the fly from DataLyzer, Microsoft Excel, Access, SQL Server, Oracle Server or any ODBC compliant database without the need to import the data.  Data can be combined from multiple data sources offering a very flexible solution to find causes of variation.

Advanced Analysis

Various analysis like Control chart analysis, capability analysis, multiple correlational analysis, Pareto Analysis, Multi-Vari analysis with F and t-test, frequency analysis can be performed in a quick an easy way with various filters and selection.

For more information please download the brochure

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.