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SUMMARY:Integrating production management and process control decisions fo
 r optimal operation in fast-changing markets
DTSTART:20160429T101500
DTEND:20160429T111500
DTSTAMP:20260408T034104Z
UID:41ee88c50014adb1fc6dd688b7e5ff51b4d5ada87a5a2903a701925a
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Michael Baldea\nBio: Michael Baldea is Assistant Profess
 or in the McKetta Department of Chemical Engineering and a core faculty me
 mber in the Institute for Computational Engineering and Sciences (ICES) at
  The University of Texas at Austin. He received his Diploma (2000) and M.S
 c. degree (2001) in Chemical Engineering from "Babes-Bolyai" University in
  Cluj-Napoca\, Romania and obtained a Ph.D. in Chemical Engineering from t
 he University of Minnesota in 2006. Prior to joining The University of Tex
 as\, he held industrial research positions with Praxair Technology Center 
 in Tonawanda\, NY and GE Global Research in Niskayuna\, NY. He has receive
 d several research and service awards\, including the NSF CAREER award\, t
 he Moncrief Grand Challenges Award\, the ACS Doctoral New Investigator awa
 rd\, the Model-Based Innovation Prize from Process Systems Enterprise and 
 the Best Referee Award from the Journal of Process Control. His research i
 nterests include the dynamics\, optimization and control of process and en
 ergy systems\, areas in which he has co-authored one book\, three book cha
 pters and over 80 peer-reviewed journal and conference articles.\nDynamic 
 market conditions and the evolving integration of chemical production with
  other industries (e.g.\, energy generation) call for a closer coordinatio
 n between production management (planning\, scheduling) and process contro
 l decisions in the operation of a chemical process. The integration of  b
 usiness decisions with dynamic information from the control layer is a dif
 ficult task owing to the range of time scales involved in making the respe
 ctive decisions\, and the corresponding need to balance long-term predicti
 on with real-time execution. In this presentation\, we focus on the “mes
 oscale” of the process decision-making hierarchy\, and report on our rec
 ent developments that allow for a closer coordination between production s
 cheduling and supervisory control systems. We introduce a new time scale-b
 ridging framework\, based on capturing the input-output behavior of the ch
 emical process in a low-dimensional model\, which is then used in scheduli
 ng calculations. We extend these concepts to the integration of scheduling
  and model predictive control\, as the most widely-used advanced control s
 trategy in industry. Furthermore\, we introduce an approach for exploiting
  historical process data in building the aforementioned scale-bridging mod
 els. We demonstrate our results on several examples\, including an industr
 y-based case study concerning the demand-response operation of an air sepa
 ration plant and an application to managing energy use in buildings.
LOCATION:ME C2 405 http://plan.epfl.ch/?zoom=20&recenter_y=5864093.7808&re
 center_x=731117.21161&layerNodes=fonds\,batiments\,labels\,information\,pa
 rkings_publics\,arrets_metro\,transports_publics&floor=1&q=MA_A1%2012
STATUS:CONFIRMED
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