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Standards have profound effects on industrial productivity, international trade, and economic growth. For latecomer countries such as China, standards, and standardization are an important means to upgrade their industrial structure. Using the framework of a sectoral system of innovation, this article leverages China's hardware industry to investigate the relationships among factors that influence the performance of industrial upgrading via standards. Expert opinions and the decision making trial and evaluation laboratory method are used to evaluate the relationships. The evaluation results show that if some firms in a system have the capability to execute standardization and innovation, with the support of the government to build and shape standardization institutions and infrastructures, the knowledge and technological capabilities of the entire industry can be enhanced, leading to the gradual introduction of high-quality standardized products into markets by firms even as they move toward more knowledge-intensive segments. This article contributes to two academic fields. First, standards are an important but often neglected topic in the innovation system literature. This article not only investigates the neglected topic but also explores the mechanism through which standards influence industrial upgrading at the meso-level. Second, several previous studies assumed that the drivers of supplier upgrades in developing countries are mostly driven by powerful buyer firms that are based in advanced countries. However, this article finds that customer requirement is not the most influential driver of the industrial upgrading of developing countries. [ABSTRACT FROM AUTHOR]

This article presents a practical approach to realize demand and energy savings in large industrial plants through behind-the-meter conservation voltage reduction implementation. Requirements of a device that can implement conservation voltage reduction in harsh industrial environments are identified. Based on the requirements, a device called stacked isolated voltage optimization module is discussed. Issues concerning the design and operation of the device are explained. Experimental results from a prototype unit are presented. [ABSTRACT FROM AUTHOR]

IIoT significantly improves industrial productivity and at the same time reduces manufacturing costs. In order to satisfy the requirements in IIoT applications, such as location awareness and low latency, edge intelligence has been proposed to enhance the capability of processing data at the edge of the network. As a typical example of edge intelligence, fog computing offers a lot of potential benefits including transient storage, decentralized computation, stronger security, and so on. In this article, we mainly focus on the data security in edge intelligent IIoT. We present four major challenges in data security of edge intelligent IIoT, including reliable storage, convenient usage, efficient search, and secure deletion, and provide the corresponding solutions to each challenge. Furthermore, we propose an optimized framework, which enjoys higher security and better integration to IIoT. The proposed framework promotes the underlying IIoT in data acquisition, processing, and transition, thus leading to stronger security and better efficiency. Finally, we implement the solutions on a desktop and Raspberry Pi, and demonstrate the experimental results. [ABSTRACT FROM AUTHOR]

Facility layout is vital to save operational cost and enhance production efficiency. Multirow layout is a common pattern in practical manufacturing environment. Although parallel machines are frequently implemented in practice to enhance productivity, there lacks any in-depth study on multirow layout problem with parallel machines. In this paper, its mathematical programming formulation is established to minimize material flow cost. A three-stage approach is proposed to solve it. First, a Monte Carlo heuristic is devised to optimize the sequence of machines on multiple rows. Second, a linear program is used to determine the optimal exact location of each machine. Finally, an exchange heuristic is adopted to reassign material flows among parallel machines in different machine groups. An iterative optimization strategy is suggested to execute the three stages repeatedly to improve the solution quality. This approach is applied to a number of problem instances and compared against others. The experimental results show that it is able to effectively solve this new problem and significantly decrease material flow cost. Note to Practitioners—Multirow layout is common in practical manufacturing systems in which parallel machines are often used to improve productivity, shorten production time, and guarantee some flexibility. This paper studies a multirow parallel machine layout problem that involves machine groups, each of which contains parallel machines. Solving it is to locate all machines at multiple parallel rows to minimize material flow cost. It is challenging because one needs to decompose material flows and determine exact locations of machines simultaneously. A three-stage approach is proposed to do so. It is applied to many problem instances. The results demonstrate that it works well for such layout problems with parallel machines. [ABSTRACT FROM AUTHOR]

Accurate alignment of the watch hand is a critical procedure in the industrial production of watches. However, compared with the traditional ideal laboratorial case, the watch-hand alignment suffers various external disturbances from the aged equipment and industrial operating conditions, which seriously influence the alignment precision. To achieve accurate watch-hand alignment in the complex industrial environment, this paper develops a robotic micromanipulation system and proposes a corresponding robust control strategy. First, a micromanipulation system with five degrees of freedom is set up and integrated with an optical microscope. Then, a set of proper machine vision methods is adopted to obtain accurate position information in disregard of the interference terms. Third, the dynamic model of the controlled watch hand is built with consideration of the external disturbances from the production environment. Since the velocity information cannot be observed accurately through the machine vision process, we design a state observer to acquire the position and velocity values for the following control strategy. After that, a sliding mode controller with the radical basis function neural network is proposed to achieve high-precision alignment while resisting the external disturbance. Finally, simulation and experimental results prove that the proposed method can realize the alignment of the watch hand within 6 s with the accuracy of $2\times 10^{-3}$ rad, which is enhanced at least two times compared with the traditional manual method. Note to Practitioners—This paper was motivated by the challenging problem of the watch-hand alignment in the industrial production. Unlike the traditional manipulation, this alignment is subjected to various disturbances from the aged equipment and complex operating conditions, including complex forces at the air–liquid operation interface and the confusing scratches, undesired flaking particles, as well as the reflection of light in the image. Here, we propose a microrobotic system and a robust control strategy to precisely align the watch hand and eliminate the influence from the above disturbances. In the machine vision process for recognizing the object, filtering, contour/corner detection, and template matching methods are adopted to acquire accurate position information despite the interference in image processing. To avoid the disturbance from the complex forces during the alignment, we develop the robust sliding mode controller to guarantee the alignment precision. The experiment results indicate that the proposed system can align the watch hand with the accuracy enhanced at least two times as previous manual method. This paper provides a general solution for micromanipulation under disturbance in industrial production environment. [ABSTRACT FROM AUTHOR]

Circuit widths and nodes of semiconductor wafers have been continually shrinking down to less than 20 nm. Therefore, modern wafer fabs enforce extremely strict process control to prevent wafer quality failures. A wafer processing chamber is now frequently cleaned to remove residual chemicals and impurities. Yu et al. show that such cleaning operations significantly change the tool operation of single-armed cluster tools, and they suggest an idea of partial wafer loading to improve the tool throughput under cleaning requirements. However, little is known about how a dual-armed tool could be effectively scheduled when chamber cleaning exists. A dual-armed robot allows more flexible tool operational sequences, and hence, the scheduling problem becomes further complicated and challenging. In this paper, we propose a scheduling method by which the dual arms can be properly exploited for better tool productivity. We show that the suggested hybrid sequence significantly reduces the tool cycle time as compared to previously developed scheduling methods. Through this research, we conclude that the productivity gain of the dual arms against single arm is more significant when chambers are cleaned. Note to Practitioners—This paper is motivated by the scheduling issues of cluster tools with chamber cleaning requirements. Though an efficient scheduling method for single-armed cluster tools is presented by Yu et al., its performance is not sufficiently close to the optimal when a dual-armed robot is considered. More specifically, we cannot expect any productivity improvement from adopting a dual-armed robot, although it allows more flexible tool operations and is known to have higher throughput than a single-armed robot. Thus, we propose a novel scheduling method for dual-armed cluster tools that require chamber cleaning operations. The experimental results show that the suggested method achieves optimal tool throughput in most of the practical tool conditions. [ABSTRACT FROM AUTHOR]

Mathematical models are often required in process modeling, control, and evaluation. To meet the increasing demand of production system real-time performance evaluation and improvement, in this paper: 1) an innovative event-based, data-driven mathematical model is established for network structured manufacturing systems; 2) important properties of network structured manufacturing systems are obtained through the concept development of a virtual ideal clean system; and 3) a system performance diagnostic method is developed based on the mathematical model and system properties, as well as available sensor data. The mathematical model and system performance identification methodology are studied analytically and validated by simulation studies. This data-driven mathematical framework and system real-time performance diagnostic methodology are invaluable for real-time production control to improve system responsiveness and efficiency. Note to Practitioners—For production systems with complex networked structure layouts, the dependence relationship between machines and buffers is more complicated compared with serial production lines. Therefore, it is more difficult to analyze and evaluate their real-time production performance such as permanent production loss. Such information is critical for real-time production management and control to achieve higher system responsiveness and efficiency. This paper establishes an event-based data-driven mathematical model to describe the real-time dynamic behavior of manufacturing systems with complex networked structures. Furthermore, an analysis method for networked manufacturing system properties and a data-driven system performance diagnostic method are proposed. The methods provide a quantitative solution to evaluate production capacity and production constraints of complex networked manufacturing systems, and to evaluate the system real-time performance such as permanent production loss and its attribution to each disruption event and machine. [ABSTRACT FROM AUTHOR]

Telecommunications service industry provides services that transmit voice, data, text, sound, video, and other signals. In the Internet age, the telecommunications service industry has experienced tremendous growth to form an indispensable infrastructure platform for today's global networked economy. In this study, we examine the output performance of telecommunications service industries in 13 Organization of Economic Cooperation and Development countries from 2000 to 2011 using the Malmquist total factor productivity index (MTFPI) as the performance metric and data envelopment analysis as the measurement approach. We further decompose MTFPI into three factors: 1) technical change; 2) pure efficiency change; and 3) scale efficiency change, that represent innovation, catch-up, and demand fluctuation, respectively. The results show that these telecommunications service industries exhibit comparatively strong productivity growth. In addition, through our decomposition analysis, it is found that telecommunications service industry is an innovator skilled at adopting technological advances that turn out to be the key driving force for the observed productivity growth. By contrast, both pure efficiency change and scale efficiency change lead to negative impacts. Based on these findings, we draw and discuss implications for telecommunications service at the country and industry levels, and provide suggestions for practice and future research. [ABSTRACT FROM PUBLISHER]

This paper studies a robotic mobile fulfillment system (RMFS) featured by robots transporting movables shelves to order pickers. The RMFS can increase productivity, reduce costs, increase order picking accuracy, and improve operational flexibility. We build queue network models to describe the RMFS with two protocols in sharing robots for pickers, propose the corresponding algorithms, conduct numerical analyses, and evaluate the performance of the RMFS by calculating the throughput time. We then calculate the optimal number and the velocity of robots, and provide the effective design rules for the RMFS. [ABSTRACT FROM AUTHOR]

Manufacturers increasingly emphasize improving product reliability and ensuring product uniformity; these two factors have become critical aspects of industrial activities. This paper describes an economic production quantity model with maintenance, production, and free-repair warranty (FRW) programs for an imperfect process. When defective parts are produced, perfect repair, inspection, and rework are conducted after the production run period. For a deteriorating production system, this paper defines an inferior item as satisfying specifications on each inspection but being likely to incur post-sale servicing costs when sold under FRW. Preventive maintenance (PM) is performed after the “in-control” production run period and can be classified as one of two types: 1) imperfect or 2) perfect. The probability of a perfect PM is calculated based on the number of imperfect PMs from the last renewal cycle. An optimal production runtime is determined by minimizing the total cost. Several special cases are discussed, including the case of maintenance learning effect. Finally, a numerical example and sensitivity analysis are reported to illustrate the model. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the replacement of a unit that is subject to a dominant failure mode. The unit is usually replaced by an age-based replacement policy, either when a preset age limit has been reached, or when failure occurs before this limit. However, the unit can also be replaced when it encounters a random production wait and its age has reached a certain threshold. Using such an opportunity for replacement can help to minimize system downtime. We formulate this joint age-based replacement limit and threshold optimization problem with the objective of minimizing the expected cost per unit time in the long run. A real-data example is presented to illustrate the applicability and effectiveness of our model. [ABSTRACT FROM PUBLISHER]

This paper presents a differential MOSFET sensor reading technique based on the bias controlled cycled measurement. The circuit was implemented, and tested with gamma radiation from a 60-cobalt source. Temperature rejection performance was assessed during the exposure in real-time measurements. The results show that in comparison with a single MOSFET dosimeter the thermal drift is 20 times smaller and the radiation sensitivity is approximately 10% higher. The switched biasing allows to extend the measurement range beyond MOSFET’s threshold voltage saturation. [ABSTRACT FROM AUTHOR]

Provides several short items that may include news, reviews or technical notes that should be of interest to practitioners and researchers. [ABSTRACT FROM PUBLISHER]

In this paper, we first show that true equipment utilizations may be significantly lower than what is recorded by existing monitoring systems in semiconductor fabrication operations, owing to various process and tool-related delays that occur during the tool “busy” or “running” state. We then demonstrate the use of a custom-developed system aimed at re-gaining the productivity loss, piloted at an Intel production facility for 300 mm 45 nm high volume manufacturing. Through a pilot case study, we present how these delays were reduced significantly (37% on average delay and 17–40% on variation in delay.) This improvement represents an equivalent of up to 4% improvement in true utilization on the pilot toolset, far more than any single project or even aggregation of projects on the roadmap for the toolset's availability improvement. [ABSTRACT FROM AUTHOR]

Yield loss associated with leakage screens is increasing as products migrate to technologies with thinner gate oxide and more aggressive lithography. Product competitiveness requires meeting low power and when products have exhausted design options, tighter than 3 sigma fast leakage screens are implemented to reduce power which can result in significant yield loss. [ABSTRACT FROM AUTHOR]

The new standard C37.118.1 lays down strict performance limits for phasor measurement units (PMUs) under steady-state and dynamic conditions. Reference algorithms are also presented for the performance (P) and measurement (M) class PMUs. In this paper, the performance of these algorithms is analyzed during some key signal scenarios, particularly those of offnominal frequency, frequency ramps, and harmonic contamination. While it is found that total vector error (TVE) accuracy is relatively easy to achieve, the reference algorithm is not able to achieve a useful rate of change of frequency (ROCOF) accuracy. Instead, this paper presents alternative algorithms for P and M class PMUs, which use adaptive filtering techniques in real time up to 10-kHz sample rates, allowing consistent accuracy to be maintained across a\pm33% frequency range. ROCOF errors can be reduced by factors of >40 for P class and >100 for M class devices. [ABSTRACT FROM PUBLISHER]

The central theme of this Special Issue is emerging opportunities and future directions in automation for green manufacturing, where information technology basedmodeling, analysis, control and optimization are the focus areas. The purpose is to show the state-of-the-art research and applications in the general area of automation in green manufacturing, by bringing together researchers and practitioners from both academia and industry, to address the significant advancement, expose the unsolved challenges, present the critical needs for integration with new technologies, and provide visions for future research and development. This Special Issue presents original, significant and visionary automation papers describing scientific models, methods and technologies with both solid theoretical development and practical importance that improve process, efficiency, productivity, quality, and reliability in green manufacturing. The contributions in this Special Issue can be divided into the following categories in green manufacturing: renewable energy products and systems; energy savings in manufacturing processes and systems; remanufacturing system design; and emission reduction in supply chain management. Specifically, the following papers are included in this Special Issue. The first category addresses renewable energy source, which includes manufacturing and operation of alternative energy products, such as batteries for electric vehicles, and system design to support manufacturing activities using renewable energy sources, such as electricity generated by wind turbines and solar panels. The second category focuses on energy savings in manufacturing, such as operational control and robot scheduling to minimize energy consumptions in production, optimal design of facility and production to reduce energy cost. The third category extends the study to remanufacturing, which plays a significant role to achieve sustainability and multiple life cycles. This includes remanufacturing system analysis, design and optimization, such as strategies for recycling, reassembly, etc. Finally, the last category considers supply chain management, within which multiple firms work together to reduce negative environmental impact. [ABSTRACT FROM AUTHOR]

Control of production operations is considered as one of the most economical methods to improve energy efficiency in manufacturing systems. This paper investigates energy consumption reduction in production systems through effective scheduling of machine startup and shutdown. Specifically, we consider serial production lines with finite buffers and machines having Bernoulli reliability model. This machine reliability model is applicable in production situations, where the downtime is relatively short and comparable to machine cycle time (e.g., automotive paint shops and general assembly). In this paper, using transient analysis of the systems at hand, an analytical performance evaluation technique is developed for Bernoulli serial lines with time-dependent machine efficiencies. In addition, tradeoff between productivity and energy-efficiency in production systems is discussed and the energy-efficient production problem is formulated as a constrained optimization problem. The effects and practical implications of operations schedule are demonstrated using a numerical study on automotive paint shop operations. [ABSTRACT FROM AUTHOR]

Editor's notes: [ABSTRACT FROM AUTHOR]

The relative failure frequency among different failure modes of a production system is referred to as failure profile in this paper. Identification of failure profile based on failure-time data collected in the production phase of a system can help pinpoint the bottleneck problems, and provide valuable information for system design evaluation and maintenance management. Major challenges of effective failure profile identification come from time-varying and limited failure-time data. In this paper, the failure profile is estimated by using the maximum likelihood method. In addition, statistical hypothesis testing procedures are proposed to inspect the existence of a dominating failure mode, and possible changes of failure profiles during a production period. The developed methods are illustrated with an automation system of a high throughput screening (HTS) process, and a production process for cylinder heads. [ABSTRACT FROM PUBLISHER]

This paper studies a multistage production scheduling problem with blocking and semi-continuous batching machine, which is abstracted from the integrated hot rolling production in iron and steel industry. One major characteristic of the problem is that the first machine is a semi-continuous batching machine that can simultaneously process multiple jobs and the jobs do not enter and leave it in a batch mode, but one by one and continuously. Furthermore, this problem considers multiple production stages of hot rolling line while previous problems in the literature focused on only the single hot rolling stage or the two stages of reheating and hot rolling. This problem can be treated as a generalized permutation flowshop scheduling problem with blocking to minimize the makespan (i.e., the maximum completion time of all jobs), which is a NP-hard problem. We formulate this problem as a mixed integer linear programming model and propose a scatter search (SS) algorithm to solve it. To further improve the performance of the SS, the reference set is divided into three parts to balance the solution quality and diversity, and a modified stochastic variable neighborhood search is developed as the local search, where two kinds of speedup strategies based on the problem's characteristics are incorporated. Computational results on practical production data and randomly generated instances of our problem show that the SS algorithm outperforms the commercial software named CPLEX and some other meta-heuristics. In addition, further tests using benchmark instances of the traditional permutation flowshop scheduling problem with blocking also demonstrate that our SS algorithm is superior to previous meta-heuristics in the literature. [ABSTRACT FROM PUBLISHER]

In this paper, we present a new sketch-based system — KnitSketch, to improve the efficiency of process planning for knitting garments at an early design stage. The KnitSketch system utilizes sketching interface with the pen-paper metaphor and users only need to draw outlines of different parts of the garment. Based on sketching understanding, the system automatically makes reasonable geometric inferences about the process-planning data of the garment. The system is designed for nonprofessional users and can design diverse garment styles by freehand drawings. The contributions of this work include contextual extraction of reusable data from sketches, a MDG structure for sketch beautification, and an integrated system with natural expression and effective communication that reduces the cognitive load of human beings. User experience shows that the proposed system helps designers focus on the task instead of the designing tools, and thus improves the efficiency and productivity of human beings. [ABSTRACT FROM AUTHOR]

This paper addresses the dynamic pricing problem of a single-item, make-to-stock production system. Demand arrives according to Poisson processes with changeable arrival rate dependent on the selling price. Item processing times follow an Erlang distribution, which allows to use the information on the production status in a tractable way. The objective is to identify a dynamic control policy that decides production and adjusts the price to maximize the long-run total discounted profit. An optimal policy is based on the so-called work-storage level that captures the information of the inventory level and the status of ongoing production process. Specifically, we show that: 1) the finished goods inventory is optimally managed by a critical stage level policy: when the inventory is below a certain work-storage level, production is started if the system is currently idle and 2) the price is optimally set by threshold levels: a certain price is posted when the work-storage level is at or below a threshold corresponding to that level of price. Moreover, we develop an efficient algorithm to compute the optimal policy. [ABSTRACT FROM AUTHOR]

In this paper, we analyze optimal scheduling of a tree-like multicluster tool with single-blade robots and constant robot moving times. We present a recursive minimal cycle time algorithm to reveal a multi-unit resource cycle for multicluster tools under a given robot schedule. For a serial-cluster tool, we provide a closed-form formulation for the minimal cycle time. The formulation explicitly provides the interaction relationship among clusters. We further present decomposition conditions under which the optimal scheduling of multicluster becomes much easier and straightforward. Optimality conditions for the widely used robot pull schedule are also provided. An example from industry production is used to illustrate the analytical results. The decomposition and optimality conditions for the robot pull schedule are also illustrated by Monte Carlo simulation for the industrial example. [ABSTRACT FROM AUTHOR]

In semiconductor manufacturing, finding an efficient way for scheduling a multicluster tool is critical for productivity improvement and cost reduction. This two-part paper analyzes optimal scheduling of multicluster tools equipped with single-blade robots and constant robot moving times. In this first part of the paper, a resource-based method is proposed to analytically derive closed-form expressions for the minimal cycle time of two-cluster tools. We prove that the optimal robot scheduling of two-cluster tools can be solved in polynomial time. We also provide an algorithm to find the optimal schedule. Examples are presented to illustrate the proposed approaches and formulations. [ABSTRACT FROM AUTHOR]

Cluster tools (also referred to as robotic cells) are extensively used in semiconductor wafer fabrication. We consider the problem of scheduling operations in an m-machine cluster tool that produces identical parts (wafers). Each machine is equipped with a unit-capacity input buffer and a unit-capacity output buffer. The machines and buffers are served by a dual-gripper robot. Each wafer is processed on each of the m machines, and the objective is to find a cyclic sequence of robot moves that minimizes the long-run average time to produce a part or, equivalently, maximizes the throughput. [ABSTRACT FROM AUTHOR]

This paper develops a methodology for eliciting shifts in preference across future scenarios in the performance assessment of infrastructure policies and investments. The methodology quantifies the robustness of alternative portfolios across a variety of scenarios and identifies the scenarios that greatly affect the assessments. An innovation of the methodology is to elicit, for each scenario, only a few relative increases or decreases in importance of selected terms of the value function, which is more efficient than a full elicitation of the value function for each scenario. The identification of critical scenarios via our methodology can be used to focus resource-intensive and potentially costly modeling activities. The methodology integrates preference orders, centroid weights, and the Borda method. In a demonstration, the methodology assesses the relative sea level and other climate-change scenarios that could affect the performance of coastal protections. [ABSTRACT FROM PUBLISHER]

Overall equipment efficiency (OEE) is widely adopted in semiconductor manufacturing to assess and enhance equipment productivity. The rate efficiency, which is a major component of OEE, is utilized to evaluate the achievement of actual production rate to the equipment's theoretical production rate. However, the rate efficiency is significantly influenced by factors beyond the equipment and, therefore, is inadequate for deciding whether a low production rate is due to the equipment itself. Such an inaccurate evaluation of production rate of equipment usually results in productivity loss. Hence, this study develops a novel metric, called running efficiency (RUNE), to compare the actual and theoretical production rates of the equipment. The RUNE is not affected by the production environment and can be employed to determine sources of equipment's variation. Additionally, a RUNE management procedure is also proposed. The management procedure incorporates an automatic target-setting scheme to set the theoretical production time of every motion in equipment to obtain the RUNE value of equipment. An exponentially weighted moving average control chart is then utilized in the management procedure to monitor the RUNE value of equipment. A real case from a 300-mm fabrication in Taiwan is employed to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In today's competitive semiconductor manufacturing environment, improving fab productivity and reducing cost requires that all systems work collaboratively towards production, quality and cost targets. Equipment engineering systems (EES), including advanced process control have risen to the top as key enablers for maximizing fab productivity, however these systems have been hindered as they focus on equipment and process, rather than fab-wide, metrics. Extending EES into the yield management space allows for leveraging yield prediction information as feedback into closing the loop around the fab to better achieve productivity goals. With this added capability of yield prediction, EES can: 1) predict yield excursions as well as excursion sources (leveraging virtual metrology technology), thereby avoiding costly post mortem yield recovery activities; 2) improve EES capabilities such as maintenance management and scheduling/dispatch; and 3) utilize yield prediction information as feedback to all levels of control in the fab, from individual processes up through factory-level controllers so that processes can be continuously tuned to meet yield and device performance targets without resorting to design changes to slower products. Case studies of application of this feedback information illustrate that benefits can be achieved from straight-forward applications, however these benefits can be expanded (especially) as more complex scheduling and control solutions are implemented. Realizing this type of yield-enhanced EES solution (YMeAPC) in a cost-effective manner requires fab-wide adherence to standards and best practices for component integration, event-based control system operation, and user interface management. [ABSTRACT FROM AUTHOR]

The article discusses the challenges that are associated with vision-based motion planning for industrial manipulators. A discussion of an approach to vision-based motion planning which was developed by the authors and is aimed at planning paths that are within the sensing and actuation limits of industrial hardware and software is presented. A vision-based motion planner which was developed by the authors and augments probabilistic road maps with vision-based constraints is discussed.

The article discusses the innovative processes that can improve the perspective of software product planning and development in the long-term for companies that are producing software-intensive systems. It cites that the absence of innovation will reduce the competitive advantage of a company and its long-term productivity will drop to diminishing returns. It presents the Star Search lightweight process that can be used to optimize the continuous use of few resources for innovation.

Bogey testing, also known as zero-failure testing, is used in industry to demonstrate reliability at a high confidence level. This test method is simple to apply; however, it requires excessive test time and/or a large sample size, and thus is often unaffordable. For some products, a failure is defined in terms of a performance characteristic exceeding a specified threshold. For these products, it is possible to measure the performance characteristic at different times during testing. The measurement data can be employed to predict whether or not a test unit will fail by the end of the test. When there are sufficient data to make such a prediction with a high degree of confidence, the test of the unit can be terminated. As a result, the test time is reduced. This paper develops a method for degradation bogey testing to reduce test time. In particular, the paper describes degradation modeling, and the calculation of the conditional failure probability of a test unit. Then we develop the optimum test plans, which choose the sample size, and the expected test time, by minimizing the total test cost, and simultaneously satisfying the constraints on the type II error and available sample size. Sensitivity analysis shows that the optimum test plans are robust against the preestimates of model parameters. The paper also presents decision rules for terminating the test of a unit. The proposed method is illustrated with an example. The application shows that the method is effective in reducing test time. [ABSTRACT FROM AUTHOR]

In this study, we apply the tripartite decomposition of productivity growth proposed by Kumar and Russell (Amer. Econ. Rev., vol. 92, pp. 527-548, 2002) to estimate and evaluate the contribution of firms' IT capital accumulation to their productivity growth. Analyzing a panel data on 52 public accounting firms in Taiwan for ten years from 1993 to 2002, our results indicate that the productivity growth of these accounting firms was primarily due to their accumulation of IT capital. In addition, our results indicate that services diversification towards nonaudit services and workforce quality contributed to accounting firms' IT capital accumulation, which, in turn, led to their productivity growth. [ABSTRACT FROM AUTHOR]

The article presents a survey of business and information technology (IT) executives in the pharmaceutical industry. It offers empirical data that provide insights into how the alignment of IT and business strategies affect the level of productivity and profitability of companies. It shows that firms with higher levels of sales, net profit margins and productivity were positively correlated with higher levels of strategic alignment maturity (SAMA).

This correspondence paper presents the validation of a formation-flight control technique with obstacle avoidance capability based on nonlinear model predictive algorithms. Control architectures for multiagent systems employed in this correspondence paper can be categorized as centralized, sequential-decentralized, and fully decentralized methods. Centralized methods generally have better performance than decentralized methods. However, it is well known that the performance of the centralized methods for formation flight degrades when there exists communication failure among the vehicles, and they require more computation time than the decentralized method. This correspondence paper evaluates the control performance and the computation time reduction of the sequential-decentralized and fully decentralized methods in comparison with the centralized method and shows that the fully decentralized method can be made effective against short-term communication failure. The control inputs for formation flight are computed by nonlinear model predictive control (NMPC). The control input saturation and state constraints are incorporated as inequality constraints using Karush-Kuhn-Tucker conditions in the NMPC framework, and the collision avoidance can be considered in real time. The proposed schemes are validated by numerical simulations, which include the process and measurement noise for more realistic situations. [ABSTRACT FROM AUTHOR]

We have used a well-known technique in wireless communication, pulse width modulation (PWM) of time division multiplexed (TDM) signals, within the architecture of a novel wireless integrated neural recording (WINeR) system. We have evaluated the performance of the PWM-based architecture and indicated its accuracy and potential sources of error through detailed theoretical analysis, simulations, and measurements on a setup consisting of a 15-channel WINeR prototype as the transmitter and two types of receivers; an Agilent 89600 vector signal analyzer and a custom wideband receiver, with 36 and 75 MHz of maximum bandwidth, respectively. Furthermore, we present simulation results from a realistic MATLAB-Simulink model of the entire WINeR system to observe the system behavior in response to changes in various parameters. We have concluded that the 15-ch WINeR prototype, which is fabricated in a 0.5-μm standard CMOS process and consumes 4.5 mW from ±1.5 V supplies, can acquire and wirelessly transmit up to 320 k-samples/s to a 75-MHz receiver with 8.4 bits of resolution, which is equivalent to a wireless data rate of ∼ 2.56 Mb/s. [ABSTRACT FROM AUTHOR]

We report the observation of performance degradation in a detector consisting of a phosphor screen and a CMOS (complementary metal-oxide-semiconductor) photodiode array under the continuous irradiation of 45-kVp x-rays. The performance was assessed in terms of dark pixel signal, dynamic range, modulation-transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). From the measurement results, it has been observed that the increase of dark pixel signal and the related noise gradually reduces the dynamic range as the cumulative input exposure to the detector increases. Severe degradation in NPS was observed, which gives rise to reduction in DQE as the cumulative input exposure increases. With carefully updated offset and gain correction, however, we can overcome the detrimental effects of increased dark current on NPS and DQE. [ABSTRACT FROM AUTHOR]

This paper addresses the speed and flux regulation of induction motors under the assumption that the motor parameters are poorly known. An adaptive passivity-based control is proposed that guarantees robust regulation as well as accurate estimation of the electrical parameters that govern the motor performance. This paper provides a local stability analysis of the adaptive scheme, which is illustrated by simulations and supported by a successful experimental validation on an industrial product. [ABSTRACT FROM AUTHOR]

During the past decade, manufacturers have invested heavily in the use of advanced manufacturing technologies (AMTs). The results of these investments have been mixed, as some organizations have seen significant returns while others have experienced major problems in implementation. As yet, the returns and complementarities between AMT have not been determined. Using complementarity assumptions developed by Milgrom and Roberts [P. Milgrom and J. Roberts, "Rationalizability, learning, and equilibrium in games with strategic complementarities," Econometrica, vol. 58, no. 6, pp. 1255-1277, 1990.1, [P. Milgrom and J. Roberts, "Complementarities and fit - strategy, structure, and organizational-change in manufacturing," J. Accounting Economics, vol. 19, no. 2-3, pp. 179-208, 1995], combined with the Survey of Advanced Technology in Canadian Manufacturing (a comprehensive AMT survey), a model of manufacturing plant productivity was developed. Constrained regression analysis reveals that the effective use of AMT depends on the types of AMT used in combination and that analysis done with a high level of aggregation of either size classes or industries will result in ambiguous conclusions. Insight into the impact of complementarities on optimal AMT adoption strategies is provided through solution lattices for medium plants and the vehicle industry. [ABSTRACT FROM AUTHOR]

In recent years, wireless location estimation has attracted a significant amount of attention in different areas. Various types of radio signals are applied for the development of location-estimation algorithms. In this paper, the range measurements acquired from the received time-based information are adopted, and the modified least square (LS) method is utilized to process the raw data and to finally locate the target object. Practical issues, such as the nonline-of-sight (NLOS) errors and the geometric dilution of precision (GDOP) effect, are of concern. The NLOS error will cause a large nonnegative bias while measuring the propagation delay, which will lead to an unreliable result for location estimation. On the other hand, a large GDOP value corresponds to a poor geometric topology, which will result in inferior performance by adopting most of the existing location algorithms. The proposed location-estimation algorithms with virtual base stations (VBSs) will both mitigate the influence from the NLOS errors by imposing the geometric constraints and reduce the GDOP effect by incorporating the assisted VBSs. Two iterative schemes are proposed, including the center-of-gravity-based VBS (VBS-CG) and the minimal GDOP-based VBS (VBS-MG) algorithms, to determine the required number and the locations of the assisted VBSs. The proposed VBS algorithms are compared with other existing location-estimation schemes via simulations. The performance of the VBS-MG algorithm is observed to outperform the other schemes, particularly under the environments with larger NLOS errors and poor geometric layouts. [ABSTRACT FROM AUTHOR]

This paper addresses the control of electrostatic parallel-plate micro actuators in the presence of such modeling errors as unmodeled fringing field effect and deformations. In general, accurate descriptions of these phenomena often lead to very complicated mathematical models, while ignoring them may result in significant performance degradation. In this paper, it is shown by finite-element-method~based simulations that the capacitance due to fringing field effect and deformations can be compensated by introducing a variable serial capacitor. When a suitable robust controller is used, the full knowledge of the introduced serial capacitor is not required, but merely its boundaries of variation. Based on this model, a robust control scheme is derived using the theory of input-to-state stability combined with back- stepping state feedback design. Since the full state measurement may not be available under practical operational conditions, an output feedback control scheme is developed. The stability and performance of the system using the proposed control schemes are demonstrated through both stability analysis and numerical simulation. The present approach allows the loosening of the stringent requirements on modeling accuracy without compromising the performance of control systems. [ABSTRACT FROM AUTHOR]

This paper analyzes 300-mm manufacturing inefficiencies that need to be addressed to improve productivity in the next-generation factory, classifies them into seven general themes, quantifies their business impacts, and identifies specific improvements needed for each as the basis for collaboration between integrated device manufacturers and equipment vendors to address the issues. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a differential Colpitts voltage-controlled oscillator (VCO), performing a signal oscillation with low phase noise. The proposed VCO is a part of our RF integrated circuit (IC) transceiver design project; some transceiver components are also introduced. VCO performance is verified both in simulation and practical measurement using the proposed RF IC transceiver, communicating with a commercial passive UhF RF identification tag in a small-scale area. The measured phase-noise level at the frequency divider output port is nearly —106 and —135 dBcIHz at 40-kHz and 1-MHz offset, respectively. A good figure-of-merit of 1.93 dB is obtained. The paper also highlights some important components [e.g., phase-locked loop, low-noise amplifier, dc offset canceller (DCOC)], and their performance. We configure the reader system, which consists of the proposed transceiver on board and a patch antenna, to use frequency hopping in 15 channels at a 200-kHz interval. The transceiver power amplifier supports 22 dBm of power. Configuring the interrogation range to 1 m, we measure received backscatters at the DCOC output port (the regenerated tag data level is 8 mV). Finally, we verify satisfactory states of the tag data process in the receiver. [ABSTRACT FROM AUTHOR]

A physically open, but electrically shielded, mi- crowave open oven can be produced by virtue of the evanescent fields in a waveguide below cutoff. The below cutoff heating chamber is fed by a transverse magnetic resonance established in a dielectric-filled section of the waveguide exploiting continuity of normal electric flux. In order to optimize the fields and the performance of the oven, a thin layer of a dielectric material with higher permittivity is inserted at the interface. Analysis and synthesis of an optimized open oven predicts field enhancement in the heating chamber up to 9.4 dB. Results from experimental testing on two fabricated prototypes are in agreement with the simulated predictions, and demonstrate an up to tenfold improvement in the heating performance. The open-ended oven allows for simultaneous precision alignment, testing, and efficient curing of microelectronic devices, significantly increasing productivity gains. [ABSTRACT FROM AUTHOR]

Information about the roundtable discussing the expectations, meaningful advances, and promising developments in electronic systems-level (ESL) design is presented. Topics include the meaning of ESL, the attempt to improve designer productivity, and improve design quality. The roundtable was participated by Rajesh Gupta, Forest Brewer, and Gerard Berry.

Telework could potentially offer significant savings on fuel, office space, and carbon emissions, improve productivity and morale and even reduce the outflow of US jobs overseas. Many companies have enthusiastically embraced it, but pitfalls loom. It appears that the public sector, especially the federal government, is behind on deploying telework opportunities. The challenges of setting up office system replicas in homes or telecenters are significant. Yet the payoffs, measured in productivity gains and real estate savings alone, could make the investment pay off handsomely. [ABSTRACT FROM AUTHOR]

With the rapid development of network technology, the potential use of networked real-time control and automation is enormous and appealing. However, closed-loop control systems via the Internet are very difficult to implement practically due to their stochastic nature. The large and random time delay and data dropout caused by data transmission impact the performance of the control system and even result in system instability. To address this problem, this paper proposes a methodology to modify and enhance the conventional system so that it can be used over the Internet. This paper describes a model-based networked predictive control scheme based on round-trip time delay measurement rather than separate consideration of the feedback channel delay (between the sensor and controller) and the forward channel delay (between the controller and actuator), which successfully avoids the requirement of synchronization. It is required by many schemes but is actually hard to achieve over the Internet. Stability for both fixed and random network transmission delays is also investigated in this paper. To illustrate the control performance improvement of the proposed control scheme, the results of off-line simulations and real-time experiments via the Internet are presented. [ABSTRACT FROM AUTHOR]

The effects of interference in the setup of wireless sensor networks (WSNs) represent a critical issue, and as such, it needs to be carefully addressed. To this aim, helpful information can be achieved through measurements to be carried out in advance on suitable prototypes and testbeds. In this paper, the measurement of industrial WSN performance is dealt with. In particular, a suitable testbed enlisting IEEE 802.15.4 wireless sensor nodes is presented along with the results of some experiments carried out even in the presence of interference. The purpose is to show how to evaluate some specific parameters of a WSN employed for industrial applications to obtain useful information for its setup optimization in the presence of interference. The analysis will show that from the measurement of these parameters (number of failed pollings, polling round-trip time, experimental cycle time, and alarm latency), interference effects can effectively be recognized, and the network setup can be optimized. [ABSTRACT FROM AUTHOR]

We consider a wireless sensor network, sampling a bandlimited field, described by a limited number of harmonics. Sensor nodes are irregularly deployed over the area of interest or subject to random displacement; in addition sensors measurements are affected by noise. Our goal is to obtain a high quality reconstruction of the field, with the mean square error (MSE) of the estimate as performance metric. In particular, we analytically derive the performance of several reconstruction/estimation techniques based on linear filtering. For each technique, we obtain the MSE, as well as its asymptotic expression in the case where the number of field-harmonics and the number of sensors grow to infinity, while their ratio is kept constant. Through numerical simulations, we show the validity of the asymptotic analysis, even for a small number of sensors. We provide some novel guidelines for the design of sensor networks when many parameters, such as field bandwidth, number of sensors, reconstruction quality, and sensor displacement characteristics, to be traded off. [ABSTRACT FROM AUTHOR]

Testing of high-resolution, digital-to-analog converters (DACs) with gigahertz clock rates is a challenging problem. The bottleneck is fast and accurate output measurement. This paper presents a novel high-performance DAC testing approach that uses a flash analog-to-digital converter (ADC) to achieve high- speed data acquisition, adopts the wobbling technique to provide a sufficient resolution, and processes the data with a sophisticated algorithm to guarantee high test accuracy. Simulation results show that, by using a 6-bit ADC and wobbling, the static linearity of 14-bit DACs can be tested to better than 1-LSB accuracy. The experimental results that are included in the paper also affirm the performance of the algorithm. This method provides a solution to both the production and on-chip testing problems of high- performance DACs. [ABSTRACT FROM AUTHOR]