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Firms in several industries, such as medicine, apparel, and publishing, must jointly determine the price and production quantity of their products well in advance of the selling season. Normative prescriptions to solve this problem have generally ignored behavioral aspects of decision making while behavioral research has paid limited attention to interdependent, multidimensional decisions. We experimentally examine subjects' performance when they jointly determine price and quantities. We find that subjects systematically deviate from the theoretically optimal price and quantity levels. Contrary to expectation, decomposing the price and quantity decisions does not improve subjects' decisions. In a series of follow-up experiments, we isolate the effects of (a) interdependence between decisions and (b) demand uncertainty. We show that decisions improve by making subjects more aware of interdependence and by reducing the uncertainty. However, reducing complexity through partial automation of the interdependent dimensions does not improve the decisions made by subjects. We also find that subjects anchor on cost for price decisions and on mean demand potential for quantity decisions, thereby explaining the consistent underpricing and overordering behavior across experiments. History: Accepted by Vishal Gaur, operations management. Keywords: multidimensional decision making * task interdependence * pricing * demand uncertainty * behavioral operations * anchoring, 1. Introduction The complexity of real decisions often arises from the fact that multiple decisions must be taken jointly under uncertainty, especially when the decisions are interdependent. For example, a [...]

The development of manufacturing tools and processes capable of precisely positioning and manipulating nanoscale components and materials is still in its embryonic stage. Microactuators are emerging as important tools capable of precisely positioning and manipulating nanoscale components and materials. This paper provides a summary of the state-of-the-art in the design, fabrication, and application of microactuators for nanoscale manufacturing and assembly. Key characteristics and design models of electrothermal and electrostatic microactuators are described and compared. Specific design requirements for their functionality at the nanoscale are discussed. The results demonstrate the limitations of existing microactuator designs and key challenges associated with their design, modeling, and performance characterization for nanoscale positioning, assembly, and manipulation. [DOI: 10.1115/1.4001662]

Nanomanipulation refers to the process of transporting nanoscale components. It has found applications in nanodevice prototyping and biomolecular and cellular investigation. In this paper, we present an atomic force microscope (AFM) based approach for automated manipulation of nanoparticles to form designed patterns. The automated manipulation is based on a novel method, successive directional push. This method keeps pushing along a fixed forward direction until the particle reaches the baseline of the target position, and it then repeats the pushing process along the baseline direction. This process is iterated until the particle reaches its target position. By examining the topography of several local parallel scan lines, this method can determine the lateral coordinate of the particle. The novelty of this method lies in the fact that further pushing along the same pushing direction can be conducted without precise information about the forward position. The successive directional push method has been successfully implemented into an AFM system. We demonstrate that complex designed patterns including over 100 latex particles of 50 nm diameter can be fabricated with this method. [DOI: 10.1115/1.4001676]

This paper describes an approach to automate the design for sheet metal parts that satisfy multiple objective functions such as material cost and manufacturability. Unlike commercial software tools such as PRO/SHEETMETAL, which aids the user in finalizing and determining the sequence of manufacturing operations for a specified component, our approach starts with spatial constraints in order to create the component geometries and helps the designer design. While there is an infinite set of parts that can feasibly be generated with sheet metal, it is difficult to define this space systematically. To solve this problem, we have created 108 design rules that have been developed for five basic sheet metal operations: slitting, notching, shearing, bending, and punching. A recipe of the operations for a final optimal design is then presented to the manufacturing engineers thus saving them time and cost. The technique revealed in this paper represents candidate solutions as a graph of nodes and arcs where each node is a rectangular patch of sheet metal, and modifications are progressively made to the sheet to maintain the parts manufacturability. This paper also discusses a new topological optimization technique to solve graph-based engineering design problems by decoupling parameters and topology changes. This paper presents topological and parametric tune and prune ([(TP).sup.2]) as a topology optimization method that has been developed specifically for domains representable by a graph grammar schema. The method is stochastic and incorporates distinct phases for modifying the topologies and modifying parameters stored within topologies. Thus far, with abovementioned sheet metal problem, [(TP).sup.2] had proven better than genetic algorithm in terms of the quality, of solutions and time taken to acquire them. [DOI: 10.1115/1.4001409] Keywords: sheet metal, graph, rule-based systems, topology, graph transformation, grammar, optimization, parametric tuning, design automation

This article develops an effective procedure for handling two-class classification problems with highly imbalanced class sizes. In many imbalanced two-class problems, the majority class represents 'normal' cases, while the minority class represents 'abnormal' cases, detection of which is critical to decision making. When the class sizes are highly imbalanced, conventional classification methods tend to strongly favor the majority class, resulting in very low or even no detection of the minority class. The research objective of this article is to devise a systematic procedure to substantially improve the power of detecting the minority class so that the resulting procedure can help screen the original data set and select a much smaller subset for further investigation. A procedure is developed that is based on ensemble classifiers, where each classifier is constructed from a resized training set with reduced dimension space. In addition, how to find the best values of the decision variables in the proposed classification procedure is specified. The proposed method is compared to a set of off-the-shelf classification methods using two real data sets. The prediction results of the proposed method show remarkable improvements over the other methods. The proposed method can detect about 75% of the minority class units, while the other methods turn out much lower detection rates. Keywords: Data reduction, detection power, ensemble classifier, false alarm rate, highly imbalanced classification, resampling, support vector machine, 1. Introduction We are concerned with developing a classification rule for highly imbalanced two-class classification problems. That is, the number of records in the minority class is a very small [...]

Consider a sequence of items produced on a high-speed mass production line which is subject to a random failure. When an item in the sequence is inspected it is possible to obtain directional information about the exact timing of a process failure--before or after producing the inspected item. Using this directional information this paper proposes Bayesian inspection procedures that deal with three related problems: (i) how often to inspect items on the production line; (ii) how to conduct the search for more defective items; and (iii) when to stop the search process and salvage the remaining items. Based on various cost factors, the problem of optimal inspection interval, optimal search process and an optimal stopping rule is formulated as a profit-maximization model via a dynamic programming approach. For the production process with an unknown failure rate, Bayesian methods of estimating the process failure rate are proposed. The proposed Bayesian inspection procedures can be applied to a wide variety of high-speed mass production processes such as printing labels, filling containers or mixing ingredients. Keywords: Inspection, search model, Bayesian estimation, renewal-reward process, dynamic programming, 1. Introduction Consider a mass production facility for printing labels, filling containers, or mixing ingredients. At the beginning of a production run, the facility starts 'in control' after initial setups [...]

With increasing demand for power and with shortages envisioned especially during the peak load times during the summer, there is a need to boost gas turbine power. In Taiwan, most gas turbines operate in combined cycle mode for base load. Only a small portion of gas turbines operates in simple cycle mode for peak load. To prevent the electric shortage due to derating of power plants during hot days, the power augmentation strategies for combined cycles need to be studied in advance. As a solution, our objective is to add an overspray inlet fogging system into an existing gas turbine-based combined cycle power plant (CCPP) to study the effects. Simulation runs were made for adding an overspray inlet fogging system to the CCPP under various ambient conditions. The overspray percentage effects on the CCPP thermodynamic performance are also included in this paper. Results demonstrated that the CCPP net power augmentation depends on the percentage of overspray under site average ambient conditions. This paper also included CCPP performance parametric studies to propose overspray inlet fogging guidelines for combined cycle power augmentation. DOI: 10.1061/(ASCE)0733-9402(2010) 136:1(11) CE Database subject headings: Taiwan; Energy consumption; Power plant. Author keywords: Inlet fogging; Overspray; Combined cycle; Power augmentation.

One of the main problems of substructure-based parallel solution methods is the imbalances in the condensation times of substructures when direct solvers are used. Such imbalances usually decrease the performance of the parallel solution. Thus, in this study, a workload distribution framework for such methods at heterogeneous computing environment is presented. The main idea behind this framework is to iteratively adjust the shapes of substructures so that the imbalance in their condensation times is minimized. Both generated and actual structural models were solved to illustrate the applicability and the efficiency of this approach. In these examples, a PC cluster having eight different computers was used. DOI: 10.1061/(ASCE)CP.1943-5487.0000019 CE Database subject headings: Structural models; Substructures; Parallel processing; Load distribution. Author keywords: Workload balancing; Partitioning; Repartitioning; Substructure; Parallel; Heterogeneous computing; PC cluster.

Multivariate process monitoring and fault detection is an important problem in quality improvement. Most existing methods are based on a common assumption that the measured values of variables are the true values, with limited consideration of the various types of measurement errors embedded in the data. On the other hand, research on measurement errors has been conducted from a pure theoretical statistics point of view, without any linking of the modeling and analysis of measurement errors with monitoring and fault detection objectives. This paper proposes a method for multivariate process monitoring and fault detection considering four types of major measurement errors, including sensor bias, sensitivity, noise and dependency of the relationship between a variable and its measured value on some other variables. This method includes the design of new control charts based on data with measurement errors, and identification of the maximum allowable measurement errors to fulfill certain fault detectability requirements. This method is applicable to processes where the natural ordering of the variables is known, such as for cascade or multistage processes, and processes where the causal relationships among variables are known and can be described by a Bayesian network. The method is demonstrated in two industrial processes. Keywords: Process monitoring, measurement errors, cascade or multistage process, Bayesian networks, regression, 1. Introduction Rapid advances in sensors and distributed sensing technologies have resulted in data-rich environments, creating unprecedented opportunities for quality improvement in many domains (Ding et al., 2006). To make [...]

The high-power millimeter-wave beams that can be generated by CW gyrotrons represent a promising energy source for rapid high-temperature processing of materials. A program is under way at the Naval Research Laboratory to investigate the heating of ceramic tubes and cylinders using an 83-GHz beam for joining and sintering applications. In this paper, we discuss the scattering and absorption of microwave power by a ceramic cylinder and calculate the resulting temperature profile. The analysis accounts for the temperature dependence of the dielectric properties, an effect that can dramatically alter the microwave coupling during the heating process. In the process under investigation, the cylinder is rotated to promote azimuthally uniform heating so that only the radial dependence of the dielectric properties needs to be included. Index Terms--Ceramics, dielectric losses, electromagnetic heating, gyrotrons, material processing.

We quantify the impact of work in process (WIP) bubbles on a semiconductor fab. As a preliminary step, we formalize the concept of WIP bubbles by decomposing them into local events of relatively acute and temporary WIP congestion. The local bubble is empirically identified and its impact on local waiting time distribution is assessed. We then estimate its marginal impact on the overall line waiting time and cost. Finally, a novel visualization tool for the bubble's progression is proposed. Index Terms--Congestion, production management, semiconductors, work-in-process.

Nanotechnology--what is it? According to the National Nanotechnology Initiative, "Nanotechnology is the understanding and control of matter at dimensions of roughly 1 to 100 nanometers, where unique phenomena enable novel [...]

The application of learning curve analysis to 80 percent of the production of the main dipoles for Large Hadron Collider (LHC) is discussed. Findings reveal higher learning percentage, which indicates a lower learning speed.

The usage of quality control systems for addressing software errors in production management is discussed.

The current trends in operational complexity of supplier-customer systems measurement are discussed.

The failure of statistical validation and fitting of nonlinear simulation metamodels in explaining the behavior of computer behavior models in operations management is proved.

Technological advance depends on funding, government research and development, improvement in computer and software quality, and is expected to accelerate in the future.

Byline: Yushun Fan (1), Wei Shi (1), Cheng Wu (1) Keywords: Integration platform; CIMS; system architecture; object-oriented technology; application programming interface Abstract: Adoption of CIMS in manufacturing enterprises requires more advanced tools for application integration. This paper presents the system architecture and services of an integration platform, CIMS Application Integration Platform for Manufacturing Enterprises (MACIP). MACIP integrates a set of application software and application development tools to provide a complete system for CIMS implementation. It includes a communication system, a global information system, three domain application sub-integration platforms, an Internet interface and an operation management and control system. It is based on the Client/Server structure, and employs the object-oriented paradigm and agent technology. System openness, scalability and maintenance are ensured by conforming to international standards and by using effective system design software and management tools. MACIP can significantly reduce the complexity of CIMS implementation. Author Affiliation: (1) Department of Automation, Tsinghua University, Beijing, 100084 Article History: Registration Date: 29/09/2004

Since the early 1980's, when Japanese manufacturing firms in a number of industries - including auto, electronics, and machinery - achieved high levels of international competitiveness, Japanese manufacturing practices - particularly those associated with just-in-time manufacturing (JIT) - have attracted considerable attention in North America. Transfer to the United States of JIT is characterized by special production management practices involving inventory and quality control, industrial relations, and supplier-manufacturer relationships. Because so many different aspects of plant operation are involved, the transfer of JIT requires a substantial effort on the part of U.S. manufacturers. Despite this barrier, anecdotal evidence suggests that substantial transfer of Japanese production methods has taken place and that this transfer has had a significant impact on the performance of U.S. manufacturing plants. However, there is little empirical evidence of this process that is based on broad samples of plants and workers from various manufacturing industries. The purpose of this paper is to help fill this gap in the literature. Using a sample of U.S.- and Japanese-owned manufacturing plants in the United States in three different industries, we show that the implementation of JIT has improved many of the performance measures for these U.S. manufacturing plants. Index Terms - Just-in-time manufacturing, manufacturing performance, production management practices.

Byline: Sergio Cavalieri (1), Paolo Gaiardelli (1) Keywords: Adaptive genetic algorithms; flow-shop; dynamic population size; simulation Abstract: This paper describes the characteristics of two hybrid genetic algorithms (GAs) for generating allocation and sequencing of production lots in a flow-shop environment based on a non-linear, multi-criteria objective function. Both GAs are used as search techniques: in the first model the task of the GA is to allocate and sequence the jobs in the second model, the GA is combined with a dispatching rule (Earliest Due Date, EDD) thus limiting its task only on the allocation of the jobs. Both GAs are characterized by a dynamic population size with dynamic birth rate, as well as by multiple-operator reproduction criteria and by adaptive crossover and mutation rates. A discrete-event simulation model has been used in order to evaluate the performances of the tentative schedules. The proposed algorithms have been subsequently compared with a classical branch and bound method. Author Affiliation: (1) Dipartimento di Economia e Produzione, Politecnico di Milano, Piazza Leonardo da Vinci,32, I-20133, Milano, Italy Article History: Registration Date: 29/09/2004

Byline: T. DIVOUX (1), E. RONDEAU (1), F. LEPAGE (1) Keywords: Information system; industrial communications; EXPRESS; MMS Abstract: The MMS standard provides a homogeneous environment for communications between manufacturing equipment. In order to harmonize the information and communication systems of a manufacturing plant, we propose to define a translator that allows generation of MMS objects from an EXPRESS analysis. We first present the MMS standard and the EXPRESS description language. We then describe the methodology that we have used. We finally show an example, which is based on our translator between these two formalisms. Author Affiliation: (1) Centre de Recherche en Automatique de Nancy (CNRS URA 821), UniversiteA' de Nancy I, BP 239, 54506, Vandoeuvre-le`s-Nancy Cedex, France Article History: Registration Date: 07/09/2004

Byline: V.V. EMELYANOV (1), S.I. IASSINOVSKI (1) Keywords: CIM; Simulation; resource; event; action; operation; discrete manufacturing system Abstract: Automated control of discrete manufacturing processes and their simulation must be based on a unified formalization, which makes it possible to describe a wide class of manufacturing systems, processes and conditions. This paper discusses an approach to creating a formalization method on the basis of artificial intelligence (AI) and the object-oriented approach. Modified production rules were chosen as such a formalism. The method of knowledge representation about manufacturing systems suggested by the authors makes it possible to create systems of control and simulation of manufacturing systems without using rigid decision-making algorithms. The use of the object-oriented approach increases the clarity and ease of manufacturing systems description for simulation. A structure of a developed production-rules-based simulator is also presented. A simple example gives an idea of the possibilities of the simulator. Author Affiliation: (1) Department of Computer-Aided Systems for Manufacturing Automation (PK-9), Moscow State Bauman University of Technology, 5 Baumanskaya 2nd Street, Moscow, 107005, Russia Article History: Registration Date: 07/09/2004