Environmental monitoring in JMP: Practical applications for reliable process control

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Environmental monitoring (EM) refers to the systematic process of measuring and controlling the cleanliness and environmental conditions within a cleanroom. It is essential for organizations that operate in regulated or high‑precision environments, such as pharmaceutical cleanrooms, semiconductor fabrication, and biotech labs, as well as consumer goods where even tiny particles or microbes can compromise product quality and safety.  Successful EM programs must detect anomalies quickly, communicate risk clearly, and support traceable, data-driven decision-making.

JMP, with its powerful interactive visualization and statistical modelling tools, offers an ideal ecosystem for building robust EM workflows. In this article, we explore how JMP can simplify EM programs, enhance data quality, and provide actionable insights that support both compliance and operational excellence.

Why environmental monitoring matters

Environmental conditions, including airborne particles, microbial counts, temperature, humidity, and differential pressure, directly impact product quality and operational safety. With an effective EM program you can:

• Identify trends before deviations occur.
• Rapidly investigate excursions with validated statistical tools.
• Demonstrate control to regulatory bodies.
• Optimize facility performance with continuous insight.
• Strengthen risk management through data transparency.

Yet EM data is rarely straightforward. It often includes skewed distributions, zeros, episodic events, nested locations, instrument variability, and seasonal effects. JMP’s visual‑first analytical approach turns these complexities into opportunities for deeper understanding.

Case study: Detecting cleanroom drift with JMP

To illustrate how these concepts play out in a real‑world scenario, let’s walk through a representative case study from a pharmaceutical cleanroom environment. While the details are fictionalized, the data behaviors, challenges, and workflow are typical of what many quality and EM teams experience.

1. Background

A pharmaceutical manufacturer operating ISO 7 cleanrooms began observing a gradual increase in environmental alerts over several months. Although all results remained within regulatory action limits, the rise in low‑level excursions indicated a potential drift in environmental control that required further assessment. With the possibility of an unannounced audit in the coming weeks, addressing the emerging trend became increasingly critical.

The EM team managed sample data from:

• Viable air plates, surface contact plates and finger touch plates
• Three different grades

Over a three‑month period, daily data were collected across 79 sampling locations, resulting in approximately 8,000 data points — an extensive dataset requiring thorough analysis.

The team used JMP to standardize the EM workflow and identify whether the alerts represented random noise or a meaningful signal.

2. Data collection, consolidation and cleaning

The first challenge was that environmental data originated from three different logging systems. To address this challenge, the team first used:

JMP Query Builder (to combine SQL and CSV data sources). Next the used Recode to unify naming conventions (e.g. Rm1, Room 1, R1). The team then established a single cleanroom monitoring data table.

3. Spatial insight: Custom floorplan heat maps

Once a dataset has been structured and harmonized, EM teams can use an addin from the JMP Marketplace to visualize results spatially with the custom floorplan heat maps. 

This approach allows:

• Cleanroom floorplans to be imported as image files
• Sampling points to be mapped to precise coordinates
• Contamination levels or particle counts to be represented as color gradients

Such visualizations offer immediate insight into spatial patterns, helping identify clusters, emerging hotspots, or areas undergoing gradual change even before action-level excursions occur.

4. Trend detection: Accelerated screening with process screening

The EM team used Process Screening to evaluate all sampling locations simultaneously across multiple parameters and to rank them by statistical significance. Notably, with the enhancements introduced in JMP 19, Process Screening now supports count‑distributed data and automatically displays alert (2‑sigma) and action (3‑sigma) limit alarms, an especially useful capability for environmental monitoring datasets. In addition, Process Screening automatically fits a number of different distributions and uses the distribution that best fits the data to determine alert and action limits for each process based on the fitted distribution.

The Process Screening results aligned seamlessly with the floorplan heat maps, confirming statistically significant upward trends at six sampling sites. By regrouping the data by sample type, cleanroom grade, and location, the team was able to pinpoint the precise sources contributing to the environmental drift. Notably, two sample types displayed increasing alarm trends, indicating the early stages of a major excursion.

To confirm the emerging trend, the significant sampling locations were selected and further examined using the control charts embedded within Process Screening. By simply highlighting the affected sample types and applying the ‘Chart as Selected’ option, the corresponding control charts were generated instantly. As a result, the team could pinpoint which sample types exhibited out-of-trend behavior and identify the specific days that major deviations occurred.

When a large number of control charts need to be reviewed, the Alarm Graph offers a streamlined way to visualize all excursions above the action limit, as well as any upward trends over the selected monitoring period. The team could easily visualize when and where contamination issues occurred.

5. Share results seamlessly with JMP Live

To be even more proactive and instead of sending screenshots and pdfs, the EM team published all results using JMP Live. It provides a centralized browser-based platform for reviewing EM trends for interactive visualizations accessible to QA, operations teams and leadership thus enhancing cross-functional visibility and supporting data-driven decision-making across departments.

Key takeaways

By integrating Query Builder, Recode, custom floorplan heat maps, Process Screening, and JMP Live, EM teams gain a streamlined, repeatable, and highly transparent workflow. The combined approach supports:

• Faster access to clean, unified data.
• Reduced manual effort and lower risk of error.
• Earlier identification of environmental shifts.
• Clearer visual communication of cleanroom status.
• Improved audit readiness and regulatory alignment.

The result is an environmental monitoring program that transitions from reactive investigation to proactive environmental oversight built on reliable, analyzable, and shareable data.