by Vern Puchalski, on October 19, 2018
Integration is the art of harmonizing hardware, software, and equipment systems in order to optimize, visualize, and automate manufacturing processes.
Automation is the art of transforming manually performed business activities into processes that are orchestrated and controlled through software solutions.
Optimization is the art of maximizing manufacturing efficiency, throughput, OEE, yield, and quality by monitoring, analyzing, and iteratively tuning manufacturing processes.
Visualization is the art of providing transparency into manufacturing, engineering, and supply chain operations in order to enable continuous optimization.
Migration is the art of exchanging critical business processes and IT systems without disrupting manufacturing operations.
A white paper is an authoritative report or guide that informs readers concisely about a complex issue and presents the issuing body's philosophy on the matter.
Best practices documents describe manufacturing IT solutions which are accepted within the manufacturing industry as being correct or most effective.
Previously recorded webinars provide in-depth discussion regarding specific manufacturing topics and solutions.
Demos are brief videos that showcase a specific aspect of a manufacturing topic or solution.
Presentations and recordings from past events hosted or attended by SYSTEMA are available to view or download.
Case studies are up-close and detailed examinations of challenges faced within a real-world manufacturing environment along with proven solutions.
Data sheets provide critical pieces of information, such as features and technical details, related to SYSTEMA’s products and services.
Blogs are informal discussions or informational pieces related to manufacturing optimization topics, solutions, and SYSTEMA-related news.
MES Models usually describe a simple UP/DOWN state for equipment. Real-world conditions require multi-dimensional states for individual lots/point-in-process-recipes. This series describes a Process Capability system to model these conditions, vary these states and deploy complex run rules simply and easily for operations staff.
Your mind is full of wonder whenever you think of the intricate equipment in your factory. Somehow your pulse quickens just looking at rows of multi-chambered tools designed to perform numerous sub-micron actions using exotic chemicals and processes. As you wonder how your factory manages to string 500 processes together to make a yielding chip, your sleep-deprived mind returns to your MES and the equipment model that allows you to describe almost none of the real-world conditions that make it all possible. If only there were a better way to control the factory other than with tribal knowledge, countless Engineering Change Notices (ECNs), personally babysitting production, and middle-of-the-night calls.
The majority of Manufacturing Execution Systems (MES) in existence allow you to model a single-state dimension on equipment. That is, the tool is “UP” or “DOWN” with no simple methods to describe the wide gulf of capability between these two states.
In reality, one machine may have 10 or more dimensions of capability that describe individual tooling, process chemicals, sensitivity, accuracy ranges, etc. They can be static (low res vs. high probe), time or activity based (i.e. individual qualification states), changeable via discrete action (tooling or process chemical change), or variable/time-varying (i.e. removal rate).
Simple, named process capabilities and a set of change actions can model these additional dimensions and accommodate complex behavior for tool control.
A named process capability requires a name, equipment association, initial state, and methods to change its state. The name should be meaningful to the operators and indicate the action required to make a lot “capable” on his or her tool. Good examples of named process capabilities include “24 HR QUAL”, “PHOTO RESIST ABC”, “LOW RES”, “THIN TEOS”. Any lot requiring these capabilities on a specific tool may be shown incapable for any of these reasons indicating that the operator must first perform a required qualification every 24 hours, change the resist bottle, use a LOW RES machine, or find a tool with thin Tetraethyl Orthosilicate (TEOS) enabled respectively.
Once the capability name is created, it can be associated with a machine at the proper point in the equipment hierarchy (i.e. a cluster tool mainframe or chamber). The initial state is assigned and state change events are added to the model.
To model the real-world state changes, we must be able to change state explicitly based on discrete events. In addition, it must be possible to set “good until” conditions. In this case you may, optionally, set timers (“good until” time) conditions, “good until” lots or units for usage-based capabilities. Most events will consume this “good until” condition but others may “set” a value (i.e. qualification complete) or “add” lots or units should you find that some recipes clean or condition the equipment in such a way as to extend capability.
To make use of the offered capabilities, you must be able to assign required conditions to the lot/recipe/equipment/operation context. Specific capabilities are required depending on the requirements of that lot on that equipment at this time.
A fully-integrated process capability system can be reflected in the lot selection process for operators clearly blocking “non-capable” from running on tools. Capability checks can be seen up and downstream to optimize dispatching decisions.
Real-world experience indicates that equipment utilization can be increased by several percent, especially at tools that require building batches of lots (like furnaces or cleaning tools), and save millions of dollars in equipment maintenance deferred by proper use of the process capability concept.
For more information regarding how to improve manufacturing efficiency by leveraging manufacturing automation solutions, check out SYSTEMA’s guide to digital transformation.