Application of a concept development process to evaluate process layout designs using value stream mapping and simulation

Purpose: We propose and demonstrate a concept development process (CDP) as a framework to solve a value stream mapping (VSM) related process layout design optimization problem. Design/methodology/approach: A case study approach was used to demonstrate the effectiveness of CDP framework in a portable fire extinguisher manufacturing company. To facilitate the CDP application, we proposed the system coupling level index (SCLI) and simulation to evaluate the process layout design concepts. Findings: As part of the CDP framework application, three process layout design concepts - current layout (CL), express lane layout (ELL) and independent zone layout (IZL) - were generated. Then, the SCLI excluded CL and simulation selected IZL as the best concept. The simulation was also applied to optimize the performance of IZL in terms of the number of pallets. Based on this case study, we concluded that CDP framework worked well. Research limitations/implications: The process layout design optimization issue has not been well addressed in the VSM literature. We believe that this paper initiated the relevant discussion by showing the feasibility of CDP as a framework in this issue. Practical implications: The CDP and SCLI are very practice-oriented approaches in the sense that they do not require any complex analytical knowledge. Originality/value: We discussed a not well-addressed issue with a systematic framework. In addition, the SCLI presented was also unique.Peer Reviewe

Proximity search heuristics for wind farm optimal layout

A heuristic framework for turbine layout optimization in a wind farm is proposed that combines ad-hoc heuristics and mixed-integer linear programming. In our framework, large-scale mixed-integer programming models are used to iteratively refine the current best solution according to the recently-proposed proximity search paradigm. Computational results on very large scale instances involving up to 20,000 potential turbine sites prove the practical viability of the overall approach

Practical Layout-Aware Analog/Mixed-Signal Design Automation with Bayesian Neural Networks

The high simulation cost has been a bottleneck of practical analog/mixed-signal design automation. Many learning-based algorithms require thousands of simulated data points, which is impractical for expensive to simulate circuits. We propose a learning-based algorithm that can be trained using a small amount of data and, therefore, scalable to tasks with expensive simulations. Our efficient algorithm solves the post-layout performance optimization problem where simulations are known to be expensive. Our comprehensive study also solves the schematic-level sizing problem. For efficient optimization, we utilize Bayesian Neural Networks as a regression model to approximate circuit performance. For layout-aware optimization, we handle the problem as a multi-fidelity optimization problem and improve efficiency by exploiting the correlations from cheaper evaluations. We present three test cases to demonstrate the efficiency of our algorithms. Our tests prove that the proposed approach is more efficient than conventional baselines and state-of-the-art algorithms.Comment: Accepted to the 42nd International Conference on Computer-Aided Design (ICCAD 2023); 8 pages, 8 figure

A hierarchical approach to energy management in data centers

Abstract — This paper concerns the management of energy in data centers using a cyber-physical model that supports the coordinated control of both computational and thermal (cooling) resources. On the basis of the structure of the proposed model and practical issues related to the data center layout and distribution of information, we propose a hierarchical optimization scheme in which the higher level chooses goals for regulation at the lower level. Linear programming is applied to solve sequences of one-step look-ahead problems at both the top level and in the lower-level controllers to solve. The approach is illustrated with simulation results. I

Automatic synthesis of analog layout : a survey

A review of recent research in the automatic synthesis of physical geometry for analog integrated circuits is presented. On introduction, an explanation of the difficulties involved in analog layout as opposed to digital layout is covered. Review of the literature then follows. Emphasis is placed on the exposition of general methods for addressing problems specific to analog layout, with the details of specific systems only being given when they surve to illustrate these methods well. The conclusion discusses problems remaining and offers a prediction as to how technology will evolve to solve them. It is argued that although progress has been and will continue to be made in the automation of analog IC layout, due to fundamental differences in the nature of analog IC design as opposed to digital design, it should not be expected that the level of automation of the former will reach that of the latter any time soon

An Integrated, Evolutionary Approach to Facility Layout and Detailed Design

The unequal-area, shape constrained facility layout problem is a NP-hard combinatorial optimization problem concerned with minimizing material handling costs. An integrated methodology that incorporates a genetic algorithm and a constructive heuristic is developed to simultaneously solve the traditional block layout problem of locating and shaping departments and the detailed design problem of locating the input/output stations of departments. These problems have received much attention over the past half-century with the majority of research focused on solving them individually or sequentially. This thesis aims to show that an integrated methodology which combines the problems and solves them in parallel is preferable to sequential approaches.The complexity of the integrated layout problem is reduced through a Flexbay formulation and through pre-assigned intra-departmental flow types. A genetic algorithm with a two-tiered solution structure generates and maintains a population of block layout solutions throughout an evolutionary process. Genetic operators reproduce and alter solutions in order to generate better solutions, find new search directions, and prevent premature convergence of the algorithm. An adaptive penalty mechanism guides the search process and reduces the computational overhead of the algorithm. Through the placement of input/output stations, the optimization of a block layout's material flow network is implemented as a subroutine to the genetic algorithm. A contour distance metric is used to evaluate the costs associated with material movement between the input/output stations of departments and aids in constructing practical aisle structures. A constructive placement heuristic places the input/output stations and perturbs them until no further improvement to a layout can be realized. The integrated approach is applied to several well known problems over a comprehensive test plan. The results from the integrated approach indicate moderate variability in the solutions and considerable computational expense. To compare the integrated methodology to prior methodologies, some of the best results from the unequal-area facility layout problem are selected from prior research and the I/O optimization heuristic is applied to them. The results of the integrated approach uniformly and significantly outperform the results obtained through sequential optimization. The integrated methodology demonstrates the value of a simultaneous approach to the unequal-area facility layout problem