[NOTE: THE DEADLINE FOR SUBMITTING ABSTRACTS HAS BEEN EXTENDED]
The theme for this year's SIGMAN workshop is "interaction and adaptation." The shop floor has become increasingly responsive to changes due to customer demands, management commitments, and new regulations. Together, such factors result in a complex set of interactions to which the shop floor operations must be adapted if the manufacturing process is to be competitive. Adding to the complexity is the volume of data concerning part quality, throughput, inventories, machine status, worker productivity, material handling, and finished goods. The assumptions and actions of one decision maker may easily conflict with the decisions of another and threaten havoc. The application of AI techniques to the practical operational problems of the shop floor provides a fertile testing ground for AI research, and the opportunity for improving shop floor operations.
TOPICS:
Representation: Given the volume of data and the complexity of interactions, how can the dynamic environment of the shop floor be represented for both efficient inferencing and human understanding?
Inference, analysis and decision-making: What mechanisms are available that allow "good enough" solutions to be generated in a fixed time period, but better solutions to be generated given longer periods of time? How can operations research and AI techniques, stochastic modeling and adaptive reasoning, reactive and proactive analyses, etc. be integrated for better operational decision-making that reflects current shop floor conditions?
Learning: What mechanisms can learn about the shop floor state and identify "cue" conditions that could trigger the application of a particular operational strategy?
Scheduling: How can shop-floor level schedules be integrated in a way that satisfies the many demands and constraints inherent in the meeting of higher-level goals?
Fault detection, isolation, and recovery: Can the onset of shop floor contingencies be detected in such a way that the effects of the problems can be isolated and plans for recovery generated?
Information management: What mechanisms can be constructed to present the human decision maker with clear and relevant information from a large volume of shop floor data? Which aspects of decision making should be computer-generated and which aspects should be left to shop floor personnel?
Regulation: Given that the shop floor is constrained by the regulations of both governments and unions as to what operations can take place and how they can be executed, what mechanism can be used to propagate constraints concerning government and union regulations through the shop floor operations, scheduling and control processes?
FORMAT: The workshop will be organized into panel discussions related to the topics specified above.
SUBMISSIONS: All interested in attending the workshop should submit three hard copies of a list of relevant publications, activities, etc. All interested in presenting papers should submit three hard copies of extended abstracts (no longer than five pages). Send all submissions by April 1, 1994 to:
Dr. Leslie Interrante (chair) Intelligent Systems Laboratory Center for Automation and Robotics University of Alabama in Huntsville Huntsville, AL 35899 interr@ebs330.eb.uah.edu 205-895-6658 FAX: 205-895-6733
Decisions regarding paper acceptances or invitations to attend the workshop will be announced by April 15, 1994. Camera-ready copies of full-length papers (of up to 12 pages of 12 point type, that includes figures, bibliography, etc.) must be received by April 29, 1994.
The workshop will be held August 4, 1994 (during AAAI94) in Seattle, WA.
Organizing Committee: Leslie Interrante (chair; interr@ebs330.eb.uah.edu), Chris Tong (co-chair; ctong@cs.rutgers.edu), David Goldstein (goldstn@ncat.edu), Hank Grant (fgrant@nsf.gov), Caroline Hayes (hayes@cs.uiuc.edu), Claude Le Pape (lepape@ilog.fr), D. Navin-Chandra (dchandra@isl1.ri.cmu.edu), Daniel Rochowiak (drochowi@cs.uah.edu), Mike Shaw (mshaw@ux1.cso.uiuc.edu), Stephen Smith (sfs@isl1.ri.cmu.edu).