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Step 2: Process Control
December 31, 1969 |Estimated reading time: 6 minutes
By Jason Spera and Vincent Dubois
Software always has been instrumental in the implementation of process control methods in manufacturing. Software made statistical process control (SPC) data collection and proactive reaction to this data viable, and real-time product tracking and process monitoring possible. Software enables fail-safe line setup and materials management. Today, the scope of manufacturing software systems includes such a range of data sources and analytical capabilities that the meaning of "process control" has evolved beyond the original definitions of SPC. Continuous quality improvement now means monitoring and validating not only the process, but validating the delivery of operator information and materials to the process, as well as automating line control based on real-time process and machine data. Software now eliminates faults in line setup, operator instructions, chemical and materials tracking, as well as the real-time process itself. This broadening process control technology minimizes all root causes of product defects.
In traditional manufacturing process control, SPC methods are implemented to detect when a process is approaching an out-of-control condition, with the objective of taking corrective action before end products be-come non-conformant. Modern process control software is extending proactive quality management beyond detecting and controlling process variability, to controlling opportunities for error in pre-process activities of the factory.
Modern process control software seeks to proactively control operational faults that lead to manufacturing defects, as well as detecting when in-process variability is out of control. Manual methods for managing operations are unreliable or inefficient, particularly in fast-changing, high-mix environments. The upcoming migration to lead-free will present further challenges to manufacturers faced with two different processes and chemistries running alongside one another in the same factory. New software systems address man-ufacturing "risks" in a comprehensive manner, extending seamlessly from the pre-process to in-process phases of production (Figure 1).
Figure 1. Comprehensive process control software eliminates faults in the pre-process and in-process phases of production.
Modern process control software, such as SPC, seeks to eliminate pre-process faults and avoid in-process ones. The functions required to achieve these objectives include information delivery, data and task validation, data collection, data analysis, and automated line control.
Pre-process fault control is the emerging technology of software process control. Consider the first step of simply delivering the proper operator documentation to the point of use. Electronic documentation is an improvement over paper releases. However, it is not controlled unless it is secured for access by operator, keyed to revision, keyed to job and work order, and keyed to the point of use in the factory. Documentation includes work instructions, current machine and quality manuals, standard practice documents, and specification control drawings. Automating the proper delivery of this information is part of a modern process control software solution.
Following documentation delivery to the factory is line setup and validation. Challenges include electronically validating operator certification to the process or equipment at hand, validating the current machinery preventive maintenance schedule, and validating the tooling being loaded into each machine per job. Such a system must guide operators through the changeover and validate component-to-feeder associations, and then feeder-to-machine location associations in a closed loop.
In electronics manufacturing, moisture sensitive device (MSD) exposure to atmospheric conditions and tracking bake and storage cycles is a large automation issue considered independently. Modern process control systems address this in concert with other pre-process setup and validation functions, as it is an important fault that could result in long-term product quality issues.
Pre-production faults may result in immediate scrap material. In other cases, the quality problems may be seen only later in the product lifecycle, such as when moisture sensitivity is not controlled, or if chemical life was nonconforming at the time of production. In either case, eliminating such risk can be efficiently achieved only through software systems, as the requirements are too vast for manual or paper-based systems. Electronically eliminating the risk of pre-process faults leaves process and quality engineers with only natural process variability as a concern.
The goal of process control software used while the process is running is detection of out-of-control processes before they compromise end product quality. Process control based on sampled data collection from the process has existed almost as long as software has been a term. What has changed involves the automatic data sources available to it, the software technology itself, and its ability to electronically control lines.
Modern software systems automatically harvest three critical sources of quality-related data from the process. The first involves machine event data from the real-time process. This information, while not used mathematically in SPC functions, is critical for informed diagnostics once SPC has revealed an out-of-control condition. When the SPC analysis indicates a process out of control, immediate access to machine event data can help engineers determine the root cause and select the appropriate corrective action.
The other two data sources are counts of actual product defects, or measurements such as placement deviations or functional test range values. Such attribute and variable data is used directly within the analytics of modern process control software, and harvesting it directly from machinery in real time enables rapid detection of drifting processes (Figures 2a and 2b).
Figures 2a and 2b. Modern SPC software monitors data trends and process capabilities.
Real-time SPC traditionally has been conducted at the point of use, or near the data source itself. Historical analysis has been done centrally through larger software systems. The technology exists today for server-based analysis engines to operate off large volumes of incoming real-time data from many factory data sources. Such systems provide real-time process control analysis, as well as historical quality analysis and reporting. This technology has eliminated the traditional delay between the real-time process and the results of SPC sampling.
Modern process control software leverages the SPC analysis results within the physical world through a variety of means. Systems may initiate changes to the product routing by notifying operators onscreen, or send electronic e-mails or pages to appropriate parties. In more severe conditions, the system may stop machines or lines electronically by sending commands to special SMEMA controllers or the machines themselves.
Controlling both pre-process and in-process phases of production benefits the manufacturer. For the product and process, the manufacturer is assured proper materials and chemical usage. Documentation and pre-production setup operations are ensured, so risk of first-run scrap and defects is eliminated. The factory also enjoys a more tightly controlled process window at each point in the flow while the product is running.
The total automation of pre-process tasks and early detection of in-process problems reduces the skills required for line operators. It also reduces or eliminates scrap due to such factors as setup of feeders, chemicals and incorrect documentation. The data and systems used for feeder setup also are valuable for real-time component consumption monitoring, which can be leveraged in the ERP systems of the company for better materials management. Such software solutions also mean that a great deal of these functions become automated, leaving higher-level analysis functions to the engineering staff.
Modern process control software systems provide near real-time electronic quality reporting. Furthermore, they answer the demand for granular traceability to product, process and component data. Finally, as the industry moves to lead-free, these systems will enable single factories to manage multiple chemistries together without risk.
Conclusion
Process control software spanning pre-process and in-process fault control can be a key ally. Assured setup operations, controlled materials and a self-monitoring process that stops automatically before producing non-conforming products can mean a formidable competitive advantage.
Jason Spera, CEO, may be contacted at AEGIS Industrial Software Corp., 220 Gibraltar Road, Horsham, PA 19044; (215) 773-3571; Fax: (215) 773-3572; Web site: http://www.aiscorp.com. Vincent Dubois may be contacted at Cogiscan, 50 De Gaspé, Suite A5, Bromont (Québec), J2L 2N8, (450) 534-2644; Fax (450) 534-0092; Web site: http://www.cogiscan.com.