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This paper presents a methodology for the optimal design of fixture layouts in multistation assembly processes. An optimal fixture layout improves the robustness of a fixture system against environmental noises, reduces product variability, and leads to manufacturing cost reduction. Three key aspects of the multistation fixture layout design are addressed: a multistation variation propagation model, a quantitative measure of fixture design, and an effective and efficient optimization algorithm. One of the challenges raised by this multistation design is that a high-dimension design space, which usually embeds a lot of local optimums, will have to be explored. Consequently, it makes a global optimality more difficult and, if an inefficient algorithm is used, may require prohibitive computing time. In this paper, exchange algorithms, originally developed in the research of optimal experimental design, are adopted and further revised to optimize fixture layouts in a multistation process. The revised exchange algorithm provides a good tradeoff between optimality and efficiency: it remarkably reduces the computing time without sacrificing the optimal value. A four-station assembly process for a sports utility vehicle sideframe is used throughout the paper to illustrate the relevant concepts and the resulting methodology. Note to practitioners-This paper was motivated by the problem of planning a fixture locator layout in a multistation assembly process. Existing approaches generally focused on planning fixture locator layouts on a single workstation. In a multistation production process, such as an automobile body assembly process, the fixture locating holes used on one station will be reused on different stations, which could cause a station-to-station coupling in variation propagation. In other words, dimensional variation could originate from fixture elements on every station, propagate along the production line, and accumulate on the final assembly. Station-wise fixture layout design may not necessarily lead to a good solution because it overlooks the variation coupling and propagation effect. In this paper, we modeled the variation propagation across multiple stations and provided a quantitative characterization of the performance of fixture layout with the p- resence of environmental noises. Then, we recommended an efficient computation algorithm to solve for the optimal fixture layout. Our results showed that the multistation layout design is different from a single station one; some intuitions gained from single-station design work may not be still valid. The current work is based on a two-dimensional, rigid panel assembly model. The extension to accommodate more sophisticated two-dimensional, complaint-part assembly processes is much needed in the future research.