Search

In performance-oriented architectural design, the use of advanced computational simulation tools may provide valuable insight during design. However, the use of such tools is often a bottleneck in the design process, given that computational requirements are usually high. This is a fact that mostly affects the early conceptual stage of design, where crucial decisions mainly occur, and available time is limited. In order to deal with this, decision-makers frequently resort to drawing conclusions from experience, and, as such, valuable insight that advanced computational methods have to offer is lost. This paper explores an alternative approach, which builds on machine-learning algorithms that inductively learn from simulation-derived data, yielding models that approximate to a good degree and are orders of magnitude faster. We focus on visual comfort of office spaces. This is a type of space that specifically requires visual comfort more than others. Three machine-learning methods are compared with respect...

Compact, multi-deep three-dimensional (3D), Automated Storage and Retrieval Systems (AS/RS) are becoming more common, due to new technologies, lower investment costs, time efficiency and compact size. Decision-making research on these systems is still in its infancy. This paper studies a particular compact system with rotating conveyors for the depth movement and a Storage/Retrieval (S/R) machine for the horizontal and vertical movement of unit loads. The optimal storage zone boundaries are determined for this system with two product classes: high- and low-turnover, by minimizing the expected S/R machine travel time. We formulate a mixed-integer non-linear programming model to determine the zone boundaries. A decomposition algorithm and a one-dimensional search scheme are developed to solve the model. The algorithm is complex, but the results are appealing since most of them are in closed-form and easy to apply to optimally layout the 3D AS/RS rack. The results show that the S/R machine travel time is significantly influenced by the zone dimensions, zone sizes and ABC curve skewness (presenting turnover patterns of different products). The presented results are compared with those under random storage and it is shown that significant reductions of the machine travel time are obtainable by using class-based storage.

Virtual metrology (VM) involves estimating a product's quality directly from production process data without physically measuring it. This enables the product quality of each unit of production to be monitored in real time, while preserving the process efficiency. Initially developed for the semiconductor industry, VM has recently been examined for use in other industrial fields. VM is enabled by components such as quality estimators and drift detectors. It enhances various industrial applications such as machine control and sampling decision systems. The literature lacks a comprehensive summary and a systematic review of the state of the art in VM. To fill this gap, this study followed a systematic methodology to conduct a complete and structured literature review of VM. This paper presents a detailed analysis of the 199 papers that we identified based on our search and selection criteria. Following our methodological framework, we assigned these papers to categories and highlighted shortcomings. Finally, we discussed VM's use in various industrial fields, underlining its potential for every manufacturing industry. This study and the proposed framework are useful for both practitioners and academicians since they raise crucial theoretical and managerial questions as well as provide suggestions for further research on this critical topic.

This paper reports a system for automatic extraction of manufacturable features from 'engineering drawings' created in CADD format. It employs the techniques of string based pattern recognition and natural language processing. Drawing entities are processed to derive feature string patterns, which are syntactically analyzed to detect the feature topology and geometry. The information of the features so detected is augmented by non-geometric data like dimensions, position, tolerances and the relevant drawing callouts. The system is capable of detecting generic classes of features like holes, pockets, steps, slots, bosses, etc. The derived information can be easily linked to the downline CAD/CAM activities in the product cycle. The system, thus, demonstrates the feasibility of design automation from CADD models.

This paper reports the design and implementation of a semigenerative computer assisted process planning system (PRICAPP) for prismatic components used in the batch production of prismatic components used in the batch production of portable electric tools. The software incorporates various modules for components representation; automatic machine, tollings and process parameter selection; setup planning; production time calculation and report generation. The user friendly software package has been developed on an IBM compatible PC/XT system. It provides a quick and less costly method of generating consistent process plans.