The Competitive Edge Research Priorities for U.S. Manufacturing (1991) / Chapter Skim
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Intelligent Manufacturing Control
Intelligent Manufacturing Control
Pages 25-53
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From page 25... ...
As processes grow in complexity and as intense, increasingly global competition drives firms more frequently to introduce products with more variations, the need to augment existing process control techniques has grown apace. This chapter describes the tight coupling of sensor technologies and microprocessor-based software systems that manifests intelligence by learning from experience and exhibiting some degree of synergy with a human interface.
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From page 26... ...
It is in this third domain, at the plant level, that economic choices are made about which avenues of process improvement to pursue in view of supply and demand, resource utilization, and other production management functions. IMC spans all three domains.
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From page 27... ...
Current sensor technology encompasses visual, ultrasonic, thermal, chemical, inertial, electrical, tactile, and audio sensors. These can be used singly or in combination to · provide highly detailed macroscopic information on dimens~on, position in space, shape, velocity and acceleration, global or local temperature, and compositional distribution; · detect a variety of other physical, chemical, electrical, optical, and magnetic properties; · probe internal macro- and microstructure to measure parameters such as grain size, texture, and the presence, size, and distribution of voids or other defects; and/or
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From page 28... ...
The need for IMC systems is being driven by the increased precision and decreased cycle times demanded by today's intense competition and by business needs for improved product quality. Given the increasing use of technology in manufacturing, and the growing volume and complexity of information and information sources, unaided human decision making is becoming less and less optimal—decisions made by people simply take too long and fail to reflect the richness of available data.
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From page 29... ...
Yet to be resolved are issues faced by early users and suppliers of such systems—issues related to data acquisition, correlation, presentation, and quality control, simulation of control decisions, learning from process disruptions, understanding process complexity, standardization in system implementation, and more efficient user training. A description of each of these issues follows.
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From page 30... ...
Because control is distributed and centralized decision making is often inefficient, IMC systems require a new type of operator and new organizational structure. The work force must be trained to use computer-based information tools to make local control decisions.
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From page 31... ...
begun and partially completed by the Industrial Technology Institute, could be a major step toward truly autonomous robotic capability.3 It is this dynamic interplay that leads to adaptation and modification of knowledge, which, in turn, opens the way to novel inquiries and greater understanding. Application of such image learning dynamics would produce truly flexible manufacturing systems that could identify or sort mixed parts or direct robotic applications in less controlled environments.
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From page 32... ...
This model must be autonomous, i.e., capable of operating with or without human intervention. An even more powerful paradigm for control exploits the human powers of perception, pattern recognition, and problem solving and the intelligent manufacturing system's ability to manipulate vast quantities of procedural knowledge.
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From page 33... ...
Adaptive control, though it responds to environmental change, is based on some fixed model of a process and is local in terms of the information it gathers and the control it exerts. IMC, in contrast, analyzes and uses historical information about its own actions, together with systemwide information from many sensors, to adjust its mode} of the world and effect novel action plans.
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From page 34... ...
Manufacturing Assumptions Manufacturing assumptions today are vastly different from those of only a few decades ago. A fundamental shift in the paradigm of production is taking place from managing materials processing to managing information in which machines are seen increasingly as extensions of the human mind.
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From page 35... ...
The fundamental business-related assumption of the new manufacturing environment is an economic representation of a world model, a complete description of contingent procedures for manufacturing control viewed from the perspectives of factory, product, and process. These descriptions may reflect different levels of abstraction and precision, but must be consistent across the hierarchy.
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From page 36... ...
for intelligent manufacturing control is developed, and the consequences of the various machineand business-related manufacturing assumptions in the areas of integration, control, and IMC. An Architecture for IMC the World Mode} Figure 2-2 shows a classical model of adaptive control.
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From page 37... ...
Returning to the example of thermostatic control, an intelligent system would attempt to identify a systematic element at work in too-rapid fluctuations in temperature. To do so, the system would need a logical model capable of representing cause and effect relationships associated with the disruption.
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From page 38... ...
At the plant level, manufacturing control consists in systematically choosing which disruptions to address. Here, an economic representation of the effects of disruptions is required to guide product and process choices for the plant.
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From page 39... ...
At both levels, control may be open loop, which requires one to recognize patterns and take action, or closed loop, which removes the human decision maker. The typical view of control presumes the existence of sensors that measure process outcomes, a mode]
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From page 40... ...
The rapid learning implicit in doing so can be facilitated by using machine intelligence as an adjunct to human knowledge. Intelligent systems foster such synergy.
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From page 41... ...
In practice, problems are more often recognized after the fact, as contingencies arise and causes are sought. Problems can only be recognized at the design stage in manufacturing environments that are well understood, which implies that they are static.
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From page 42... ...
The concept of the logical cell (introduced with Figure 2-1, and expanded upon in the wire-drawing case and implicit in the chemicals case) provides a structure for searching process control data bases and for controlling process parameters through closed-Ioop feedback.
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From page 43... ...
The typical automated plant will probably still have two pickling machines, but only 10 dry-wire drawing machines, one heat-treating installation, 500 wet wire-drawing machines, and 50 finishing lines {representing a 95-percent decrease in dry-wire drawing and heat-treating equipment, and a 50-percent decrease in wet-wire drawing machines and finishing linesl. When all of these microprocessor-controlled machines and the processes that run on them are integrated under a hierarchical control structure a decision maker will be able to track every process parameter that operates on every meter of wire that goes through the line.
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From page 44... ...
The decision maker can use this information in both day-to-day production decisions and in the development of aIgorithms to create new process capability over the long term. The systemwide structure of IMC permits a plant to be organized into virtual cells for problem solving.
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From page 45... ...
Wet Wire-Drawing Machines Cl Cabling Machines 111 IMC Provides Precise l l l Measures of Strands Coming Out of Wet Wire-Drawing Machines, Allowing Strands to Be Selectively Combined to Produce Cable of Precise Gauge FIGURE 2-5 Vertical logical cell used to enhance control across machines of the same type.
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From page 46... ...
; · object-oriented modeling; · multiple, integrated views of project design data, including an integrated dynamic process model; · a standard interface that allows transfer of dynamic data between the plant control system and the CAD system; · expert systems that provide embedded explanations of deposition; sign concepts and current states of control systems; · fiber optic sensing with embedded diagnostics; · chemometrics with neural computers providing on-line com· global access to process data; and · natural language translators. These technologies provide the operator's only view of processes that take place entirely within pipes and tanks" the notion of operating from behind a wall.
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From page 47... ...
The system has already automatically sent a priority electronic mail message to the analyzer specialist. The operator asks the system to predict the cost of the analyzer outage and is told that the model-based control system is compensating well but significant degradation in quality is likely.
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From page 48... ...
The engineer, wondering what effect this would have on reactor effluent composition, obtains from the plant control system flow data from that part of the real process for the past two months and uses the data to drive a simulation embedded in the conceptual design. The results suggest a problem, and operator and engineer decide to send the conceptual design, together with the plant data, back to corporate engineering design.
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From page 49... ...
An information structure using these techniques, and operating in an uncertain, dynamic world cannot be built on machine intelligence alone; human-machine integration is essential. This synergy between people and machines must yield knowledge acquisition techniques that are capable of supporting rapid start-up.
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From page 50... ...
to integrate data, pattern recognition, and action models. Transparent aigorithmic structures that facilitate ease of understanding and change and guide algorithmic development are very important for diffusion of the technology.
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From page 51... ...
In summary, research in IMC should aim at: · developing technique-oriented communication standards to facilitate the diffusion of IMC; · refining sensor technology in the areas of data integration, pattern recognition, and actionable models; · building knowledge bases of design, manufacturing, and management intelligence that can adapt to changing knowledge and organizational structures; · creating a dynamic world mode} of manufacturing; · identifying ways to utilize the human-machine interface to facilitate learning in an integrated environment; and · redefining its methods to accommodate holistic research in a production environment the factory as laboratory. MECHANISMS FOR DIFFUSION AND IMPLEMENTATION Some of the larger Fortune 100 companies, in industries most threatened by foreign compent~on or in process industries that already use a high degree of closed-Ioop feedback control, may develop and build IMC systems independently.
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From page 52... ...
Machine builders, using mechatronics, built sophisticated systems for large companies with specialized needs rather than general purpose systems for the larger body of small users, for whom the infrastructure for effective and easy use of a technology is as important as the technology itself. IMC systems, by their very nature, integrate all of the process steps in a manufacturing plant and require deep knowledge of each of those steps, so that any program that does not simultaneously build the infrastructure for the development of intelligent systems along with generic software for system integration will fail.
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From page 53... ...
Harvard Business School Working Paper No.
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