Process Control


The Industry’s first dynamic decision support system

Product configurator

Gemini™ MxG5xx

Sensor version
Ionization chamber
Emmision current
Flange connection to vacuum chamber
Switching function
Electrical connection
Digital interface
Analog output signal
Your configuration
Gemini™ MxG5xx
Switching functions
Electrical Connection
FCC, 8-pin
Digital Interface
Measurement range
1.2 - 8.68 V
Personal information
Gemini™ MxG5xx
Gemini™ MAG500
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FabRecover provides dynamic, real time maintenance decision support, as well as visibility to maintenance history, to maximize tool availability and minimize support costs.

INFICON supports the adoption of Best Known Methods (BKM), continuous improvement and enhanced visibility into maintenance activities.

First Time Right Maintenance

A knowledge-based, decision support software platform specifically designed to help factories return tools to production quickly and correctly.

Responsive and heuristic guidance provided in all use cases will reduce variability through real-time support based on subject matter expertise gathered from across the organization.

Complete activity tracking gives visibility into maintenance work, thereby supporting cycles of learning and continuous improvement through data-driven analysis and review

Preventative Maintenance (PM)

step-by-step, dynamic guidance and needed support for BKM work

Corrective Maintenance (CM)

root cause analysis and identification based on historical and heuristic data trends

Out-of-Control Action Plans (OCAP)

modeled linkage between control system events, troubleshooting, and remediation

Scheduled Maintenance

Preventative Maintenance support begins with improved First Time Right (FTR) success by reducing maintenance execution variability. FabRecover provides the tools to detail necessary work including reference materials, input validation and business rule definition.

Reduced training costs, along with increased efficiency and efficacy, stem from supporting users across the spectrum of experience and training in following Best Known Methods collected from across the organization.

Flexible and dynamic workflow definition also responds to different situations as they happen, whether addressing additional challenges or taking advantage of unexpected opportunities within each maintenance session.

Unscheduled Maintenance

Decision networks help to inform root cause investigations with historical trends and corresponding corrective actions to provide insight into current investigations.

Expert knowledge can be modeled to produce optimal investigation paths to reach known conclusions. Heuristic learning paired with dynamic guided support actively identifies the more or most likely root causes for precision and efficiency in root cause identification.

Reporting of answer history and problem resolution, including rework loops and multiple correct conclusions, builds a data set upon which to improve future efforts and effect data-driven heuristic improvements to unanticipated maintenance activities.

Expert driven solutions

Reduced development and training costs are possible through the Visual Designer and its user-friendly visual modeling platform. Subject Matter Experts (SME) are empowered to model smart business logic themselves — without code or prerequisite experience. No loss of information in translation of specs between SME and IT becomes the new standard in solution development.

Out-of-the-box use case templates lower barriers to entry in creating maintenance workflows, and can be extended to address common needs and/or enforce prescribed standards of each individual customer.

Extensibility of the platform ensures that the platform can grow to meet specific customer challenges, and that incremental development can be leverages immediately across all use cases.

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