Statistical Process Control (SPC)

Quality Intelligence on Real-time data for a better process control

Cantier SPC with the intelligence capability collect data real-time, analyzes data based on user defined tests, and helps draw conclusions. Hence manufacturers make data-driven decisions to improve product quality, reduce risk, and to meet compliance requirements. With the machine learning intelligence features, Cantier SPC provides Predictive Quality based on the historical data.

Since the 1920’s, manufacturers of products around the world have seen the need to use applied statistical methods to understand inherent process variation, reduce it and control it.

In today’s complex manufacturing processes, a tremendous amount of data is typically available. Collecting, organizing, analyzing, and presenting data that can be used by decision makers from the operator up to the plant manager, represents a huge challenge for the manufacturer.

On the collection side of the equation, the Cantier SPC can acquire data through IIoT gateway to the metrology equipment and tools. It acquires data inputs from PLCs, Industrial PCs, PC based programs like MS Excel, CSV Files, Text files and other formats.

While on the analysis side of the equation, Cantier QMS can help you sense of the data using several analysis tools. Examples include Frequency Distribution, Control Charts, Run Charts, Pareto Charts, MultiVar Charts, etc.

Key Features

Collection, extraction, and exporting of data

All standard variable control charts (i.e. Vbar R, XbarS, etc)

Descriptive statistics (i.e. Xbar R, S, Cp, Cpk, Skewness, Kurtosis, etc.)

Graphical representation (i.e. Frequency Distribution, Pareto, etc.)

Monitors key independent and dependent variables from the process

Provides history if a quality accident occurs to speed root cause analysis

Continuously acquires data from the metrology system, lab equipment, and other sources you define, at a time interval you specify

Automatically calculates control chart limits for the operator or manufacturer

Automatically analyzes each data point and tests for out of control

Auto notification via screen, email, or SMS if an out of control condition is detected

Automatically stop the equipment when Out of Control occurs.

Brings up OCAP for execution of predetermined action plans and Benefits

Key Benefits

Helps the manufacturer understand common cause versus special cause variation

Helps the manufacturer know when to react and not to react to process variation

Keeps the manufacturer aware of the process capability for individual processes

Helps a resource limited factory prioritize continuous improvement efforts

Detects discrepant product and scrap reduction

Provides needed data for internal, customer, or third-party audits

Reduce Scrap and Cost

Use data to accelerate down the path of Continuous Improvement

Automatically stop the equipment when out of control

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