Guide
The ultimate guide to managing your PI System Download now
Use your existing PI System data to find unstable process behavior, reduce variation, and improve process consistency.
THE CHALLENGE
Small shifts in temperature, pressure, flow, speed, or other operating conditions can reduce process performance without triggering an alarm.
Teams often find the problem only after yield drops, quality moves off target, or operators compensate manually.
Without a structured way to analyze variation, it is difficult to know which process variables deserve attention.
1
Define the process objective
Select a production line, unit, or process where yield or consistency needs improvement.
2
Identify critical variables
Work with process experts to identify the PI tags most likely to influence performance.
3
Analyze process variability
Use historical PI data to identify shifts, trends, instability, and relationships between operating conditions and outcomes.
4
Prioritize improvements
Identify the variables and operating ranges with the strongest opportunities to improve process consistency and yield.
THE SOLUTION
Use PI data to find and reduce process variability
Tycho works with your engineering and operations teams to analyze historical PI data and identify process variables that contribute to inconsistent performance.
We use statistical process control and statistical quality control methods to separate normal variation from meaningful process changes.
The result is a focused set of opportunities to improve process stability, reduce variability, and increase yield.
PROCESS STABILITY
Find where the process is not operating consistently
Use statistical methods to identify shifts, trends, and abnormal variation in critical process variables.
What this includes:
Identify unstable variables
Detect process shifts
Find recurring variation
Focus engineering investigation
YIELD DRIVERS
Find process conditions associated with better performance
Compare operating conditions against production outcomes to identify variables that may influence yield.
What this includes:
Identify important process variables
Compare high- and low-yield periods
Find operating patterns tied to performance
Prioritize optimization opportunities
OPERATING WINDOWS
Understand where the process performs best
Use historical performance to identify operating ranges associated with more stable and consistent production.
What this includes:
Compare operating ranges
Find conditions associated with better yield
Identify excessive process variation
Support operating target improvements
COMMON USE CASES
Where SPC / SQC analysis helps
Yield improvement
Find process variation associated with lost production.
Process consistency
Reduce differences between runs, batches, or shifts.
Quality improvement
Identify process conditions that contribute to off-target product.
Operating window optimization
Find conditions associated with more stable performance.
Root cause analysis
Narrow the process variables most likely to explain poor performance.
Continuous improvement
Give engineering teams data-backed opportunities for optimization.
BUSINESS IMPACT
The business impact of reducing process variability
Increase yield
Reduce process variation that contributes to production loss.
Improve consistency
Keep critical process variables closer to their desired operating range.
Reduce waste and rework
Identify process conditions that contribute to poor-quality production.
Focus engineering effort
Prioritize the variables with the strongest relationship to process performance.
Use existing data
Create value from PI history without deploying another process data collection system.
Frequently Asked Questions
Get answers to common questions here
DELIVERABLES
A typical SPC / SQC engagement can include:
Process variability assessment
Statistical analysis of critical PI tags
Control charts and process stability analysis
Comparison of high- and low-performing periods
Identification of potential yield drivers
Recommended areas for engineering investigation
Final findings and improvement workshop
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