THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

Nature-inspired metaheuristics comprise a compelling family of optimization techniques. These algorithms are designed with the idea of emulating some kind natural phenomena (such as the theory of evolution, the collective behavior of groups of animals, the laws of physics or the behavior and lifestyle of human beings) and applying them to solve complex problems. Nature-inspired methods have taken the area of mathematical optimization by storm. Only in the last few years, literature related to the development of this kind of techniques and their applications has experienced an unprecedented increase, with hundreds of new papers being published every single year. In this paper, we analyze some of the most popular nature-inspired optimization methods currently reported on the literature, while also discussing their applications for solving real-world problems and their impact on the current literature. Furthermore, we open discussion on several research gaps and areas of opportunity that are yet to be explored within this promising area of science.

From ants to whales: metaheuristics for all tastes

Abrasive jet machining (AJM) is a manufacturing technology based on erosion localization and intensification AJM has a progressively important influence on the machining technology market Over the past 20 years, there has been an exponential growth in the number of papers that discuss AJM Various innovations and process developments such as intermittent, submerged, thermally assisted and other jet conditions were proposed This paper examines AJM’s technological advantages and the variety of machining operations in different industries where AJM is utilized Particular attention is devoted to the micro-texturing capabilities of powder blasting and its application in tribology New evidence of ductile and brittle material removal mechanisms are reviewed together with recently discovered elastic removal mode The effects of hydraulic, abrasive and machining parameters on particles kinetic energy, machined surface roughness and footprint size are described in detail Nozzle wear has a strong dependence on nozzle materials, its geometry, particles size, hardness, and flow rate The trend of AJM development is a shift from macro to micro scale Improvements in micro-machining resolution, process controlling and erosion prediction are current challenges facing AJM

Recent advances and challenges of abrasive jet machining

Energy efficiency and environmental issues have been largely neglected in logistics. In a traditional supply chain, the objective of improving energy efficiency is targeted at the level of single parts of the value making chain. Industry 4.0 technologies make it possible to build hyperconnected logistic solutions, where the objective of decreasing energy consumption and economic footprint is targeted at the global level. The problems of energy efficiency are especially relevant in first mile and last mile delivery logistics, where deliveries are composed of individual orders and each order must be picked up and delivered at different locations. Within the frame of this paper, the author describes a real-time scheduling optimization model focusing on energy efficiency of the operation. After a systematic literature review, this paper introduces a mathematical model of last mile delivery problems including scheduling and assignment problems. The objective of the model is to determine the optimal assignment and scheduling for each order so as to minimize energy consumption, which allows to improve energy efficiency. Next, a black hole optimization-based heuristic is described, whose performance is validated with different benchmark functions. The scenario analysis validates the model and evaluates its performance to increase energy efficiency in last mile logistics.

Real-Time Decision Making in First Mile and Last Mile Logistics: How Smart Scheduling Affects Energy Efficiency of Hyperconnected Supply Chain Solutions

Characterization and optimization of Abrasive Water Jet Machining parameters of aluminium/tungsten carbide composites

In the last decade, numerous new materials are rapidly emerging and developed; it creates considerable interest in the researcher to search out the optimum combination of machining parameters during machining of these materials using advanced machining processes (AMP). In this work, an experimental investigation is carried out on abrasive water jet machining (AWJM) process for the machining of material AA631-T6 using the Taguchi methodology. Parameters such as transverse speed, standoff distance and mass flow rate are considered to obtain the influence of these parameters on kerf top width and taper angle . Regression models have been developed to correlate the data generated using experimental results. Seven advanced optimization techniques, i.e., particle swarm optimization, firefly algorithm, artificial bee colony, simulated annealing, black hole, biogeography based and non-dominated sorting genetic algorithm are attempted for the considered AWJM process. The effectiveness of these algorithms is compared and found that bio-geography algorithm is performing better compared to other algorithms. Furthermore, a non-dominated set of solution is obtained to have diversity in the solutions for the AWJM process. The result obtained using the Taguchi method and optimization techniques are confirmed using confirmation experiments. Confirmatory experiments show that both the optimization techniques and Taguchi method are the effective tools in optimizing the process parameters of the AWJM process.

Experimentation investigation of abrasive water jet machining parameters using Taguchi and Evolutionary optimization techniques

Selection of parameters for advanced machining processes using firefly algorithm

In manufacturing industries, the facility layout design is a very important task, as it is concerned with the overall manufacturing cost and profit of the industry. The facility layout problem (FLP) is solved by arranging the departments or facilities of known dimensions on the available floor space. The objective of this article is to implement the firefly algorithm (FA) for solving unequal-area, fixed-shape FLPs and optimizing the costs of total material handling and transportation between the facilities. The FA is a nature-inspired algorithm and can be used for combinatorial optimization problems. Benchmark problems from the previous literature are solved using the FA. To check its effectiveness, it is implemented to solve large-sized FLPs. Computational results obtained using the FA show that the algorithm is less time consuming and the total layout costs for FLPs are better than the best results achieved so far.

Unequal-area, fixed-shape facility layout problems using the firefly algorithm

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Multi-objective facility layout problems using BBO, NSBBO and NSGA-II metaheuristic algorithms

Abrasive water jet machining (AWJM) has found its application in the manufacturing industries for machining hard materials with precision. A degree of high precision in machining of complex geometries makes AWJM valuable. The selection of optimum process parameters is important to the resulting quality of machined parts. In this study, an experimental investigation was conducted to evaluate the machinability of Inconel 600. A response surface methodology (RSM) is used to determine the influence of the AWJM process parameters on the considered performance characteristics, i.e., kerf top width (KTW) and taper angle. The analysis of variance is performed to obtain the contribution and influence of each process parameter on the considered responses. The value of R-Squared obtained for KTW and taper angle using regression model is 0.97 and 0.96 respectively. The optimum setting of the parameters for single and multiple response characteristics are obtained using the desirability analysis of RSM. The results obtained using desirability analysis of RSM is validated by conducting the confirmation experiments. The experimental confirmatory values obtained for the considered performance parameters KTW and taper angle as 27.138 and 0.125 respectively. The corresponding value of error obtained as 0.383 and 0.013 respectively. Further, an optimum set is obtained with KTW as 27.461 mm and taper angle as 0.582° for multiple response optimisation.

Dinesh Singh

Papers

Experimentation investigation of abrasive water jet machining parameters using Taguchi and Evolutionary optimization techniques

Selection of parameters for advanced machining processes using firefly algorithm

Unequal-area, fixed-shape facility layout problems using the firefly algorithm

Multi-objective facility layout problems using BBO, NSBBO and NSGA-II metaheuristic algorithms

Investigation of kerf Characteristics in Abrasive Water Jet Machining of Inconel 600 using Response Surface Methodology