Quality Data Analytics

Empower end users with self-service analysis and interactive data visualization. Integrated intuitive statistical engineering analysis tools give users the insight to fully understand process and product quality.

Based on statistical process control methods, Predisys Analytical Suite represents a revolutionary new generation of quality control and quality management applications.

Gain insight into manufacturing operations with real-time data
and improve operational decision making to achieve better business outcomes.

SPC Software

Predisys provides a comprehensive set of real-time SPC software products. Our web-centric solution takes Quality Control from the ‘PC’ to the ‘internet age ‘ and features a modern and intuitive user interface. The solution scales across the enterprise and supply chain, with governance and security built-in.

Statistical Process Control | Analytics | Quality Control

Predisys develops quality control, test data management and manufacturing business intelligence solutions for companies seeking to optimize product quality and process efficiency, reduce the cost of compliance, and enhance manufacturing visibility across the product life cycle and supply chain.

Its flagship solution, Predisys Analytical Suite, comprises of tools for collecting and managing quality and performance measurement data from multiple data sources for analysis and reporting, using powerful statistical process control (SPC) methods and robust statistical, analytical and data visualization tools. It is the ideal software for turning vast amounts of inspection and test data into actionable information.

Predisys’ enterprise solution for medical device, diagnostics, biotech and pharmaceutical companies is FDA compliant and facilitates a cost-effective, flexible and surprisingly simple transition from paper-based records to a fully automated system for electronic management of inspection and quality data records and for product and lot traceability. The solution can be combined with Predisys Analytical Suite to provide real time SPC and visibility, enabling continuous improvement of products and processes.

1/8 Customers

"A key benefit of the new tool is that the soldering process data is now available on the PC screen of any ABB employee who needs this information."

Tuukka Lintula, Quality Manager

"Applied Materials, Inc. is the global leader in precision materials engineering solutions for the semiconductor, flat panel display and solar photovoltaic industries."

"In addition to our compliance responsibilities, we need to demonstrate that the production process always reflects the customer’s wishes"

Eric Pettes, Vice President of Quality and Regulatory Affairs, Nypro

"Predisys gives us the information we need in compact and easy-to-read format. It is a real tool in preventing negative trends"

Hans-Stefan Heimberger, Project Manager Quality for Porsche AG

"Since Predisys solution was deployed, the first pass yield in our mass production line has improved dramatically."

Jouni Lehtinen, Factory Manager

"Having all the needed data in the database, where everyone can access it easily, has freed work capacity on the shop floor to the actual production process"

Ilppo Korhonen, VP Production, Valmet Automotive

"I believe our investment lowers cost of quality and that the time to return on investment will be very short"

Jussi Kalunki, Director, IT Development, Vaisala

"Predisys allows us to rapid react to any deviations and address issues before they affect our customers"

Ian Docherty, Engineering Group Leader

Predisys Analytical Suite is the first SPC software for Microsoft SharePoint.

Together, Predisys Analytical Suite and Microsoft SharePoint provide unrivalled opportunities for manufacturers who want to go beyond traditional statistical process control software and fully embrace modern, extendable Process Analytical and IT technology for significantly improved quality control at reduced costs.

Web based SPC Software for Microsoft SQL Server Reporting Services (SSRS)

SQL Server Reporting Services (SSRS) provides a full range of ready-to-use tools and services to help you create reports for your organization. Combined with Predisys' SPC software you can now easily add statistical process control functionality, incl. a rich set of SPC control charts and statistics to your reports.

April 02, 2019
Predisys Releases Predisys Analytical Suite v4.9

Predisys Inc, a global provider of Quality Control, Test Data Management and Analytical solutions, today announced availability of Predisys Analytical Suite v4.9. The new version introduces significant new data collection capabilities, new statistical process control and visual analytical functionality as well as expanded IT-platform support making it the ideal solution for enterprises who have outgrown their legacy SPC software and need a modern quality control and analytics solution for the Industry 4.0 era.
March 29, 2019
Predisys to exhibit at ASQ World Conference, May 2019

The theme of this years ASQ World Conference is "Leading Change". This year the conference will be held May 20 to May 22, 2019 at the Fort Worth Convention Center in Fort Worth, Texas
August 24, 2018
Predisys Appointed As a Microsoft Gold Partner

Predisys today announced its appointment as a Microsoft Application Development Gold Competency Partner. The status was granted recognizing Predisys’ achievements in product technology and customer satisfaction.

Advanced SPC and Quality Data Analytics

Create Powerful, Flexible Reports with SPC & Analytics

Empower Your Users

Improve Quality

Quality Data Analytics

Advanced SPC

Process Intelligence

SPC Software

Statistical Process Control | Analytics | Quality Control

1/8 Customers

SPC for SharePoint

Predisys Analytical Suite is the first SPC software for Microsoft SharePoint.

SPC for Microsoft SSRS

Web based SPC Software for Microsoft SQL Server Reporting Services (SSRS)

News

Predisys Releases Predisys Analytical Suite v4.9

Predisys to exhibit at ASQ World Conference, May 2019

Predisys Appointed As a Microsoft Gold Partner

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