Optimal Layout Design in Multipurpose Batch Plants

Abstract

Plant layout is concerned with the spatial arrangement of processing equipment, storage vessels, and their interconnecting pipework. Deciding a good layout is an important activity in the design of chemical and process plants. A good layout will facilitate a correct operation of the plant. It will also provide an economic acceptable balance between the often conflicting constraints deriving from safety, environment, construction, maintenance, operation, space for future expansion, and process relationships such as those determined by gravity flow. This paper presents a mathematical formulation for addressing the problem of allocating items of equipment in a given two-or three-dimensional space. The objective function to be minimized is the total pumping, connection, and floor construction cost. Detailed cost factors are used to account for the flow direction between two connected units. The problem is formulated as a mixed integer linear programming model. Specific attention is paid to constructing a formulation which is suitable for the solution of large scale problems. The method presents the rigorous solution of problems with about 30 process equipment and of essentially unlimited size problems when the rigorous optimization is combined with simple heuristic rules. Three case studies are presented to illustrate the applicability of the proposed approach to retrofit problems in multipurpose plants. Trade-offs between capital and operating costs are captured so that the optimal number of required floors may be determined.

Continuous-Domain Mathematical Models for Optimal Process Plant Layout

“…The motivating example used here was introduced in ref and then considered in ref . The characteristics of the problem are summarized in Figures and .…”

“…Finally, a mixed-integer linear programming (MILP) formulation was presented in ref , considering the allocation of equipment items to floors and the detailed layout of each floor. The formulation was based on space discretization into a set of candidate locations, with each equipment item occupying one and only one location.…”

Multi-Floor Facility Layout Problems Solving by the Differential Evolution Method

“…The researchers have used many methods to solve problems. If using mathematics with exact methods (Georgiadis et al, 1997;Patsiatzis and Papageorgiou, 2002;Hahn et al, 2010;Afrazeh et al, 2010 andHa andLee, 2016) for finding the optimal solutions, a lot of time will be spent on calculation with more variables and limitations. Because the optimal solution is not easy to reaching they are many heuristic approaches (Kaku et al, 1988;Meller, 1992;Bozer et al, 1994;Meller and Bozer, 1997;Matsuzaki et al, 1999;Irohara and Goetschalckx, 2007;Chang et al, 2006) have been developed to get the near-optimal solutions such as Genetic algorithms (Kochhar, 1998;Kochhar and Heragu, 1999;Lee et al, 2005;Berntsson and Tang, 2004) simulated annealing (Meller and Bozer, 1996;Xiaoning and Weina, 2011) tabu search (Abdinnour-Helm and Hadley, 2000).…”

An approach to solve the facility layout problem based on the worst-case scenario

“…For this reason, several mathematical models have appeared to improve equipment allocations where the cost is typically minimized. These plant layout models have resolved one-floor (Barbosa-Póvoa, Mateus, & Novais, 2001;Georgiadis, Schilling, Rotstein, & Macchietto, 1999), 2D multi-floor (Jayakumar & Reklaitis, 1994Papageorgiou & Rotstein, 1998;Patsiatzis & Papageorgiou, 2002), and even 3-D ( Barbosa-Póvoa, Mateus, & Novais, 2002;Georgiadis, Rotstein, & Macchietto, 1997;Westerlund, Papageorgiou, & Westerlund, 2007) problems.…”