Implementation of P-graph modules in undergraduate chemical engineering degree programs: experiences in Malaysia and the Philippines

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• 作者：Hon Loong Lam^a ; ^{honloong.lam@nottingham.edu.my" class="auth_mail" title="E-mail the corresponding author} ; ^{honloong.lam@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Raymond R. Tan^b ; Kathleen B. Aviso^b
• 关键词：P-graph ; Process network synthesis (PNS) ; Optimization ; Engineering education ; Curriculum
• 刊名：Journal of Cleaner Production
• 出版年：2016
• 出版时间：10 November 2016
• 年：2016
• 卷：136
• 期：part_PB
• 页码：254-265
• 全文大小：2446 K

文摘

The process graph (P-graph) framework was introduced in the early 1990s as a graph theoretic approach to Process Network Synthesis (PNS) problems in chemical engineering. This framework has several advantageous features, such as mathematically rigorous generation of maximal structures (i.e., superstructures), elucidation of combinatorially feasible solution structures, and efficient search of solution space for optimal PNS compared to conventional branch-and-bound algorithms for mixed integer linear programming (MILP) models. In the three decades since its inception, the P-graph framework has proven to be a viable approach to a wide array of PNS and other structurally analogous problems; the methodology has also matured, as evidenced by the development of key software tools (PNS Draw, PNS Studio and P-graph Studio) and its appearance in modern textbooks. Nevertheless, the P-graph framework has yet to achieve broad, mainstream penetration among grassroots chemical engineering users, especially those without a strong mathematical programming background. In this paper, we discuss the implementation of instructional P-graph modules in undergraduate chemical engineering degree programs at the University of Nottingham, Malaysia Campus and De La Salle University, Manila, Philippines. These modules have primarily focused on the design of Green Processes. Results show that the visual nature of the P-graph methodology is an advantage for practical engineering decision-making, and that it complements the learning of mainstream techniques such as mathematical programming.