Traditional virtual power plants (VPPs) combine power from distributed energy resources (DER) to supply energy to users. However, they fall short of net-zero goals because of neglecting carbon footprints during power aggregation. This paper proposes a novel intelligent virtual power plant framework (iVPPF) to address this gap. iVPPF comprises a central iVPP (iVPP$_{\mathrm {C}}$) and several regional iVPPs (iVPP$_{\mathrm {n}}$), n = E, S, M, and N. These iVPPn are geographically distributed systems for intelligently managing iVPPs in four regions: east, south, middle, and north, respectively, while the iVPPC is responsible for dispatching power across iVPPn. We built iVPPC and iVPPn on individual green power clouds, which can provide abundant computing resources and realize intelligence through AI technologies for iVPPF. We also design universal computing devices called cyber-physical agents (CPAs) to collect essential data on manufacturing, carbon footprint, and energy usage for iVPPn. iVPPn can intelligently control DERs based on the collected data. Also, iVPPF can empower enterprises to participate in power balancing services offered by Taipower, thereby enhancing the flexibility of the overall power grid. Furthermore, we integrate iVPPF with the I4.2-GiM framework, offering intelligent carbon and energy management capabilities to achieve the net-zero goal. The testing results show that iVPPF can significantly reduce energy usage (up to 25.6%) and carbon emissions (up to 509 kg) through power dispatch. Thus, the proposed iVPPF promises to contribute economic benefits for businesses and the pursuit of net-zero emissions. Note to Practitioners—This paper proposes an intelligent virtual power plant framework$({i} \text { VPPF})$consisting of a central coordinator$({i}\text {VPP}_{\text {C}})$and distributed regional managers (${i}\text {VPP}_{\text {n}}$for East, South, Middle, and North). Leveraging green power clouds, both${i} \text { VPP}_{\text {C}}$and${i}\text {VPP}_{\text {n}}$harness AI for intelligent management and power dispatch across regions. We detail the system architecture and showcase practical applications, including scenarios like dispatching and aggregating for demand response, using the IEEE 13-node test feeder. Additionally, we explore the design of green power clouds and cyber-physical agents (CPAs).

Industry 4.0 is accelerating, with manufacturing enterprises embracing digital transformation and intelligent manufacturing (iM) to enhance competitiveness. Manufacturing enterprises must also improve their environmental performance to meet the goal of net zero by 2050 and to avoid border carbon tax imposed by large economies. Thus, green intelligent manufacturing (GiM), i.e., conducting iM while pursuing to maximize energy conservation and carbon reduction, has become the key development trend and a fundamental challenge for the modern manufacturing industry. To address the challenges of green intelligent manufacturing (GiM), this paper proposes a novel framework called Industry 4.2 for GiM (I4.2-GiM). This framework builds on the Intelligent Factory Automation ($i$FA) platform, which the authors developed to achieve zero-defect manufacturing (i.e., Industry 4.1). I4.2-GiM uses various IoT devices, called Cyber-Physical Agents (CPAs), to collect and integrate large amounts of data. It also includes two interrelated systems, an intelligent carbon emission management system ($i$CMS) and an intelligent energy management system ($i$EMS), simultaneously tackling carbon reduction and energy saving. Existing factory EMSs typically save less than 10% of energy, but I4.2-GiM has been shown to conserve 10.9% of energy and reduce carbon emissions by 12.55% while conducting iM in daily production. I4.2-GiM is a promising new framework that can help manufacturing enterprises approach net zero intelligently.Note to Practitioners—This paper proposes a new green intelligent manufacturing (GiM) framework called I4.2-GiM (Industry 4.2 for GiM). I4.2-GiM builds on the Intelligent Factory Automation ($i$FA) platform, which the authors developed to achieve zero-defect manufacturing (i.e., Industry 4.1). I4.2-GiM also uses various IoT devices called Cyber-Physical Agents (CPAs) to collect data from multiple sources. It also includes two interrelated systems, an intelligent carbon emission management system (iCMS) and an intelligent energy management system (iEMS), to address carbon reduction and energy saving simultaneously. Moreover, this paper provides a systematic implementation procedure and several practical examples to help practitioners adopt the designs and niches of I4.2-GiM and build their desired GiM systems for reaching the goal of net zero.

In automated production, resilience describes a system’s capacity to absorb disturbances by reconfiguring itself, thus retaining its Overall Equipment Effectiveness at least partially. This includes online behavior reconfiguration to automatically recover from or prevent faults, collectively called fault handling. Promising research exists for fault handling in automated Production Systems. In process engineering, fault diagnosis and automatic parameter adaptions are already industrially available. However, handling faults in discrete manufacturing requires a series of distinct operations, which cannot be achieved by parameter changes alone. Further, core requirements must remain fulfilled by automatic fault handling approaches, including real-time control and extra-functional requirements like changing operation modes, monitoring interlocks, and an alarming and communication system. This article proposes a concept for reconfigurable IEC 61131–3 software for automatic fault handling, validated by a public reference implementation for a demonstrator, an industrial production system, and a modified industrial test rig. Eight experiments were successfully conducted, showcasing four use cases of the concept: The prevention of faults by avoiding anomalous components, the recovery from a fault state to automatic operation, the definition of previously undefined state variables, and the monitoring of global interlocks to trigger a controlled stop. All mentioned extra-functional requirements are fulfilled. Note to Practitioners—Identification, reporting, diagnosis, and recovery of faults in automated production incur substantial effort. Project-specific code is required for diagnosis, and the recovery and re-initialization are often performed manually. To our knowledge, automatic recovery approaches from scientific literature are not widely used in discrete manufacturing. Reasons may include a frequent disregard of extra-functional requirements mentioned above. Further, some approaches are incompatible with IEC 61131–3 or industry-typical software modularization. This article proposes a PLC software concept that aims to be compatible with real-world challenges and solutions. The functional software is vertically modularized from organizational hardware-level code. The horizontal modularization separates devices or equipment groups. Support for multiple changing operation modes including two types of controlled stop (run to completion or abort), alarming, data exchange, and global interlocks are incorporated. A prototypical IEC 61131–3 implementation is publicly available that separates a reusable generic part from hardware-specific and project-specific code. The resulting control code is highly reusable, such that all modes (derived from PackML), including dynamic reconfigurations, are composed from the same software modules. Note that we do not expect the concept to be well-adoptable in continuous processes, as elaborated in the Preliminaries section.

Recounts the career and contributions of Peter Luh.

In the Laser Powder Bed Fusion (L-PBF) process, 3D components with complex geometries are fabricated in a layer-by-layer fashion by using a controlled laser beam to selectively melt particular regions of the metal powder bed. However, due to the stochastic nature of the L-PBF process, the top surface roughness of each solidified layer tends to be different even when the optimal processing conditions for the different positions on the build plate are employed. As a result, the mechanical properties of the built components frequently vary from one component to the next. Accordingly, this study proposes an Intelligent Additive Manufacturing Architecture (IAMA) for controlling the surface roughness of each build layer through an appropriate adjustment of the laser re-melting parameters. The IAMA architecture comprises five modules, namely In-Situ Metrology (ISM), Ex-Situ Metrology (ESM), Automatic Virtual Metrology (AVM), Additive Manufacturing Simulation (AMS) and Intelligent Compensator (IC). The feasibility of the proposed architecture is demonstrated by comparing the top surface roughness of cubic and mechanical strengths of tensile test samples built using the proposed method with those built using a traditional L-PBF approach without surface roughness control. It is found that the samples fabricated using the IAMA approach have an average top surface roughness of$1.6~\mu \text{m}$and a standard deviation is$0.7~\mu \text{m}$. By contrast, the samples produced using the traditional L-PBF approach have an average surface roughness of$13.45~\mu \text{m}$and a standard deviation of$2.5~\mu \text{m}$. In addition, the specimens produced with the assistance of IAMA architecture have an average tensile strength of 1013 MPa with a standard deviation of 69.5 MPa, while those printed without surface roughness control have an average tensile strength of 903 MPa with a standard deviation of 101.4 MPa Note to Practitioners—As L-PBF produce part in a layer-by-layer manner, therefore, the roughness on the top surface of previous layer have a strong influence on the printing quality of current layer. The variations of surface roughness will lead to the fluctuation of mechanical properties of the fabricated components. Additionally, to the best of author’s knowledge, current commercial L-PBF machines can not actively control the surface roughness of samples during the process. The proposed IAMA in this work can predict and control the roughness on the top surface of each layer during L-PBF process. Therefore, the constructed architecture has strong potential for integrating into the commercial L-PBF machine for controlling the surface roughness on the top of the parts during the manufacturing process. As a result, the quality of the fabricated components is expected to be in consistent. Accordingly, L-PBF machine equipped with IAMA will have a strong potential in applying for mass production of the components in aerospace and automobile industries.

Most traditional industries or emerging countries may not be capable of directly transiting to Industry 4.0. To fill the gap between as-is Industry 3.0 and to-be Industry 4.0, some disruptive innovations from automation and industrial engineering identify best practice with adopting cost-effective semi-automated systems to manage the potential socio-economic impacts of infrastructure disruptions, while considering total resource management for sustainability. This is the so-called “hybrid strategy (HS),” or “Industry 3.5.” On the other hand, the current Industry 4.0-related technologies should also emphasize quality enhancement to achieve “zero-defect manufacturing (ZDM),” also referred to as “Industry 4.1.” ZDM is a systematic strategy to realize the goal of Zero Defects, which includes two phases. Phase I: accomplish Zero Defects of all thedeliverablesby applying efficient and economical total-quality-inspection techniques; and Phase II: further ensure Zero Defects of all theproductsgradually by improving the yield with big data analytics and continuous improvement. Both the challenges and opportunities from HS to ZDM have significantly expanded the scope of traditional automation science and engineering.

Many core technologies of Industry 4.0 have gained substantial advancement in recent years. Digital Twin (DT) has become the key technology and tool for manufacturing industries to realize intelligent cyber-physical integration and digital transformation by leveraging these technologies. Although there have been many DT-related works, there is no standard definition, unified framework, and implementation approach of DT until now. Widely developing DTs for the manufacturing industry is still challenging. Thus, this paper proposes a novel implementation framework of digital twins for intelligent manufacturing, denoted as IF-DTiM, which possesses several distinct merits to distinguish itself from previous works. First, IF-DTiM fully utilizes new-generation container technology so that DT-related applications and services can be packaged in a self-contained way, rapidly deployed, and robustly operated with the capabilities of failover, autoscaling, and load balancing. Second, it leverages existing intelligent cloud manufacturing services to realize the intelligence for DT externally in a scalable and plug-and-play manner instead of using traditional approaches to embed intelligence in DT. Third, IF-DTiM contains Product DT for products, Equipment DT (i.e., EQ DT) for equipment, and Process DT for production lines, which can generically fulfill the demands and scenarios to achieve intelligent manufacturing for various manufacturing industries. Testing results show that IF-DTiM can achieve remarkable performance in rapid deployment and real-time data exchanges of DT-related applications. Finally, we develop an example DTiM system for CNC machining based on IF-DTiM to demonstrate its efficacy and applicability in facilitating the manufacturing industry to build their DT systems.Note to Practitioners—Developing Digital Twin (DT) systems to realize intelligent manufacturing is challenging. The proposed IF-DTiM (Implementation Framework of Digital Twins for Intelligent Manufacturing) provides a novel container-technology and cloud-manufacturing-service-based systematic methodology for building DTiM. In this paper, we present the system architecture and several operational scenarios (e.g., how to create and use DTs) of IF-DTiM, together with the design of its core functional mechanisms (e.g., rapid deployment scheme for DT, real-time data exchange for DT, DT interface pattern, and general workflow architecture for DT). Also, an example DTiM system for CNC machining based on IF-DTiM is presented to facilitate the practitioners to adopt the designs and niches in IF-DTiM to build their desired DTiM systems.

The concepts of Industry 4.1 for achieving Zero-Defect (ZD) manufacturing were disclosed inIEEE Robotics and Automation Lettersin January 2016. ZD of all the deliverables can be achieved by discarding the defective products via a real-time and online total inspection technology, such as Automatic Virtual Metrology (AVM). Further, the Key-variable Search Algorithm (KSA) of the Intelligent Yield Management (IYM) system developed by our research team can be utilized to find out the root causes of the defects for continuous improvement on those defective products. As such, nearly ZD of all products may be achieved. However, in a multistage manufacturing process (MMP) environment, a workpiece may randomly pass through one of the manufacturing devices with the same function in each stage. Different devices of the same type perform differently in each stage, where the performances will be accumulated through the designated manufacturing process and affect the final yield. KSA can only identify the influence of univariate variables (i.e., single devices) on the yield, yet it cannot detect the manufacturing paths that have significant influence on the yield. In order to cope with this deficiency such that the golden path with a better yield amongst all the MMP paths can be found, this research proposes the Golden Path Search Algorithm (GPSA), which can plan golden paths with high yield under the condition of the number of variables being much larger than that of samples. As a result, it makes the improvement of manufacturing yield be more comprehensive.Note to Practitioners—Traditional scheduling only considers the capacity of the manufacturing devices for allocation; while, the impact on the yield is rarely considered. In fact, in a production process, the production deviations will be gradually accumulated and affect the product quality along with the processing influence of each device. Therefore, the purpose of this paper is to propose the GPSA scheme to quickly search for high-yield manufacturing paths before the production. Manufacturers can then configure production devices based on these paths. According to the experimental results of real manufacturers’ data, GPSA can not only quickly nail down the high-yield paths from a large amount of historical data, but also alert the users to avoid paths that are prone to defective rates for their reference.

Quality control is the key for the widespread adoption of metal additive manufacturing (AM). However, online quality estimation is challenging because high-frequency stream data derived from in situ metrology have to be processed in a timely manner to figure out the complicated interactions among material, machine, and part. To tackle such issue, this article proposes an intelligent AM metrology (IAMM) architecture to decouple and evaluate quality variations caused by material properties, machine issues, and process parameters when building an AM part. The IAMM architecture can also estimate the online layer-to-layer quality (e.g., roughness and density of an AM part) by applying the robust parameters derived from the uniform design (UD) method via the enhanced automatic virtual metrology technology in a parallel computing environment, as soon as the microfeatures of melt-pools and the macrofeatures of each layer are extracted. In addition, the associated indices and features in the IAMM architecture can also be used to evaluate the defects caused by machine issues in the given process parameters. The results of case studies validate the applicability of the IAMM architecture and show that the proposed estimation models are prospective for future closed-loop control in an AM process.

The 13 papers in this special section were originally presented at the 2014 International Conference on Automation Science and Engineering (CASE 2014), held on August 25-29, 2014 in Taipei, Taiwan.

Reducing the sampling rate to as low as possible is a high priority for many factories to reduce production cost. Automatic-Virtual-Metrology (AVM) based Original Intelligent Sampling Decision (Original ISD) scheme had been previously developed for reducing the sampling rate and sustaining the VM accuracy. However, the desired sampling rate of the Original ISD scheme is fixed and set manually. Hence, whenever the VM accuracy gets worse, it cannot dynamically increase the desired sampling rate in the Original ISD scheme. As a consequence, it would take more time to collect enough samples for improving the VM accuracy. Moreover, when the VM accuracy performs well all the time, it cannot automatically decrease the desired sampling rate in Original ISD, which may result in unnecessary waste. Accordingly, this paper proposes a preliminary study of a Dynamic ISD scheme to dynamically and automatically modify the sampling rate online and in real time. The Dynamic ISD scheme can monitor the VM accuracy on line as well as update the VM models in real time for maintaining the VM accuracy when the VM accuracy becomes poor. Also, the Dynamic ISD scheme can automatically reduce the sampling rate while the VM accuracy performs well.

Wafer inspection plays a significant role in monitoring the quality of production wafers. However, it requires measuring tools and additional cycle time to do real metrology, which is costly and time-consuming. Therefore, reducing sampling rate to as low as possible is a high priority for many factories to reduce production cost. The most common way for inspecting process quality is to apply periodic sampling. If a manufacturing process is stable, then virtual metrology (VM) may be applied for monitoring the quality of wafers while real metrology is unavailable. Nevertheless, if a production variation occurs between periodic samplings, no real metrology is available during this period for updating the VM models, which may result in un-reliable VM predictions. The authors have developed the automatic virtual metrology (AVM) system for various VM applications. Therefore, this paper focuses on applying various indices of the AVM system to develop an Intelligent Sampling Decision (ISD) scheme for reducing sampling rate while VM accuracy is still sustained.

In high-tech plants, the manufacturing stability and product quality are monitored through periodic sampling. As for those non-sampled workpieces, their quality is commonly monitored by a fault detection and classification (FDC) method. Nevertheless, it may fail to detect out-of-control (OOC) products if their corresponding manufacturing process parameters are all in-spec. In other words, unless those certain defected workpieces are selected for sampling measurements, they may not be detected through simply monitoring all the individual manufacturing process parameters. We have proposed a product quality fault detection scheme (FDS), which utilizes the classification and regression tree (CART) to build a single failure model (FML) for identifying the relationship between process parameters and OOC products. However, all the failure modes (FMs) are contained in the single FML, which makes it difficult to understand the causes of defected products. To remedy this problem, this paper develops an advanced fault detection scheme (AFDS). The AFDS builds the corresponding FM by CART for each individual failure cause and generates a FM manager via support vector machine (SVM) to manage all the FMs. Finally, the dual-phase concept is adopted to run the AFDS for achieving on-line real-time fault detection.

Because virtual metrology (VM) can achieve real-time and on-line total inspection, it is a promising way for measuring machining precision of machine tools. However, the machining processes possess the characteristics of severe vibrations. Thus, how to effectively handle signals with low signal/noise ratios and extract key features from them is a challenging issue for successfully applying VM to the machine tools. In this paper, a novel VM scheme for predicting machining precision of machine tools is proposed based on several previously developed methods for data quality evaluation, model reliance evaluation, and machining precision prediction. Besides, for data preprocess, we propose a Wavelet-based de-noising method to improve the S/N ratio of sensor data. In addition, we base on the stepwise technique to develop an automatic feature selection method that can extract key features related to machining operations in time, frequency, and time-frequency domains, and can reduce the dimension of essential features. Testing results of a 3-axis CNC machine center machining standard workpieces show that the VMS can achieve the performance that the maximum average error of machining-precision conjecture is less than 2 um and the conjecture of 20 machining-precision items can be completed within 3.8 sec.

Virtual Metrology (VM) is a method to conjecture manufacturing quality of a process tool based on data sensed from the process tool and without physical metrology operations. Historical data is used to produce the initial VM models, and then these models are applied to operate in a process drift/shift environment. The accuracy of VM highly depends on the modeling samples adopted during initial-creating and on-line-refreshing periods. Since design-of-experiments (DOE) may not be performed due to large resources required, how could we guarantee stability of the models and predictions when they move into these unknown environments? Conventionally, static-moving-window (SMW) schemes with a fixed window size are adopted during the on-line-refreshing period. The purpose of this paper is to propose a dynamic-moving-window (DMW) scheme for VM model refreshing. The DMW scheme adds a new sample into the model and applies a clustering technology to do similarity clustering. Next, the number of elements in each cluster is checked. If the largest number of elements is greater than the predefined threshold, then the oldest sample in the cluster with the largest population is deleted. Test results show that the DMW scheme has better on-line conjecture accuracy than that of the SMW scheme.

Virtual Metrology (VM) is a method to conjecture manufacturing quality of a process tool based on data sensed from the process tool and without physical metrology operations. VM has now been designated by the International SEMATECH Manufacturing Initiative and International Technology Roadmap for Semiconductors as one of the focus areas for the next-generation factory realization roadmap of the semiconductor industry. This paper defines the VM automation levels, proposes the concept of automatic virtual metrology (AVM), and develops an AVM system for automatic and fab-wide VM deployment. The example of automatic VM model refreshing for chemical vapor deposition (CVD) tools is also illustrated in this paper. The AVM system has been successfully deployed in a fifth-generation thin-film-transistor-liquid-crystal-display (TFT-LCD) factory in Chi Mei Optoelectronics (CMO), Taiwan.

Selection schemes between neural-network (NN) and multiple-regression (MR) outputs of a virtual metrology system (VMS) are studied in this paper. Both NN and MR are applicable algorithms for implementing virtual-metrology (VM) conjecture models. A MR algorithm may achieve better accuracy only with a stable process, whereas a NN algorithm may have superior accuracy when equipment property drift or shift occurs. To take advantage of both MR and NN algorithms, the simple-selection scheme (SS-scheme) is first proposed to enhance the VM conjecture accuracy. This SS-scheme simply selects either NN or MR output according to the smaller Mahalanobis distance between the input process data set and the NN/MR-group historical process data sets. Furthermore, a weighted-selection scheme (WS-scheme), which computes the VM output with a weighted sum of NN and MR results, is also developed. This WS-scheme generates a well-behaved system with continuity between the NN and MR outputs. Both the CVD and photo processes of a fifth-generation TFT-LCD factory are adopted in this paper to test and compare the conjecture accuracy among the solo-NN, solo-MR, SS-scheme, and WS-scheme algorithms. One-hidden-layered back-propagation neural network (BPNN-I) is applied to establish the NN conjecture model. Test results show that the conjecture accuracy of the WS-scheme is the best among those solo-NN, solo-MR, SS-scheme, and WS-scheme algorithms.

Over the past few years, the virtual metrology (VM) technology has been proposed and developed and several VM related papers have been published. These proposed VM architectures are mainly applied for conjecturing single-stage or direct processing quality. However, the processing quality of some of manufacturing processes cannot be measured directly. Those single-stage VM architectures may not be applied to handle this indirect VM problem accurately. To properly handle this indirect VM problem, the paper proposes a dual-stage indirect VM architecture (DIVMA), which involves two process tools, to handle the indirect VM problem. In Stage I, the direct VM model of the fore-tool is established as usual, and then the indirect VM model of the rear-tool is built in Stage II that involves the Stage-I VM output. The concept of virtual cassette is also proposed in the paper. The chemical vapor deposition (CVD) process of a fifth generation TFT-LCD fab in Chi Mei Optoelectronics Corporation (CMO), Taiwan is adopted to test and compare the conjecture accuracy without and with the virtual cassette and the proposed DIVMA. Experimental results demonstrate that the virtual-cassette concept is valid for improving VM conjecturing accuracy; also this DIVMA is adequate for handling the indirect VM problem that has a coupling effect between those two subsequent tools.

In current semiconductor and TFT-LCD factories, periodic sampling is commonly adopted to monitor the stability of manufacturing processes and the quality of products (or workpieces). As for those non-sampled workpieces, their quality is usually monitored by such as a fault-detection-and-classification (FDC) server. However, this method may fail to detect defected products. For example, a workpiece with all the individual manufacturing process parameters being in-spec may still result in out-of-spec product quality. Under this circumstance, unless this certain defected workpiece is selected for sampling by chance, it cannot be detected by simply monitoring the manufacturing process parameters collected from the production equipment. To solve the above mentioned problem, this research proposes a product quality fault detection scheme (FDS), which utilizes the classification and regression tree to implement a model for identifying the relationship between process parameters and out-of-spec products. Through this model, each set of normal manufacturing process parameters can be real-time and on-line examined to detect failure or defected products.

This work proposes an advanced key-variable selecting method, the neural-network-based stepwise selection (NN-based SS) method, which can enhance the conjecture accuracy of the NN-based virtual metrology (VM) algorithms. Multi-regression-based (MR-based) SS method is widely applied in dealing with key-variable selecting problems despite that it may not guarantee finding the best model based on its selected variables. However, the variables selected by MR-based SS may be adopted as the initial set of variables for the proposed NN-based SS to reduce the SS process time. The backward elimination and forward selection procedures of the proposed NN-based SS are both performed by the designated NN algorithm used for VM conjecturing. Therefore, the key variables selected by NN-based SS will be more suitable for the said NN-based VM algorithm as far as conjecture accuracy is concerned. The etching process of semiconductor manufacturing is used as the illustrative example to test and verify the VM conjecture accuracy. One-hidden-layered back-propagation neural networks (BPNN-I) are adopted for establishing the NN models used in the NN-based SS method and the VMconjecture models. Test results show that the NN model created by the selected variables of NN-based SS can achieve better conjecture accuracy than that of MR-based SS. Simple recurrent neural networks (SRNN) are also tested and proved to be able to achieve similar results as those of BPNN-I.

Processing quality of thin film transistor-liquid crystal display (TFT-LCD) manufacturing is a key factor for production yield. In general, the processing quality of production equipment is not only related to its own manufacturing process but also affected by the process result of the previous equipment. Current proposed virtual metrology (VM) architectures are all applied to conjecture processing quality of a single stage. These single-stage VM architectures lack the ability of detecting the processing drift occur between different stages. This paper proposes a novel dual-stage VM architecture for quality conjecturing that involves two pieces of equipment. The architecture consists of two stages. In Stage I, the fore-equipment VM model is established as usual and then the rear-equipment VM model that depends on stage-I VM output is built in Stage II. An example of the proposed dual-stage VM architecture applied to two sets of TFT-LCD chemical vapor deposition (CVD) equipment is presented. Experimental results demonstrate that this dual-stage VM architecture is promising for TFT-LCD manufacturing.

A method for evaluating reliance level of a virtual metrology system (VMS) is proposed. This method calculates a reliance index (RI) value between 0 and 1 by analyzing the process data of production equipment to decide if the virtual metrology result is reliable. A RI threshold is also defined in this method. If a RI value is higher than the threshold, the conjecture result is reliant; otherwise, the conjecture result needs to be further examined. In addition to the RI, the method also proposes process data similarity indices (SIs). The SIs are defined to evaluate the degree of similarity between the input set of process data and those historical sets of process data used to establish the conjecture model. Two kinds of SIs are included in the method: global similarity index (GSI) and individual similarity index (ISI). Both the GSI and ISI are applied to assist the RI in gauging the reliance level and locating the key parameter(s) that cause major deviation, hence the VMS manufacturability problem is resolved. An illustrative example with 300-mm semiconductor foundry production equipment in Taiwan is demonstrated in this work. The real experimental results show that this method is applicable to the VMS of (such as semiconductor and TFT-LCD) production equipment.

The foundry business model was first developed by TSMC in 1985. A foundry should provide customers with IC manufacturing services. Those customers include IC design houses, integrated device manufacturers (IDM), and system suppliers. However, most electronic products are consumer products, and their life cycle has been reducing with time. An IC design house needs to continuously develop ICs with new functions to meet the current market demand for consumable products. Meanwhile, to support customers for high speed and low cost end product development, foundry service providers must also continue developing new process technologies, from 0.25mum down to 32nm. Unfortunately, advances in new manufacturing process technologies also create difficulties in new IC design. These advances increase the IC design failure rate. Currently, no effective working model and system exists to solve this problem. To formulate this high IC design failure problem, this work proposes a novel engineering-chain (EC) business model. This work also proposes an engineering chain management system (ECMS) to help achieve the goals of EC, such as improving IC design success rate, reducing IC design cycle time, lowering IC design costs, and increasing revenue.

To reduce cost, this paper proposes a system architecture to simulate and assess the multivariate of equipment properties. The architecture integrates the Monte Carlo simulation, the neural network model and the sensitivity analysis to construct a virtual metrology system. By assuming the property's probability distribution, the architecture generates the extreme input data to supplement the actual data for enhancing the model accuracy and estimating the property trend. An industrial case applied to validate the proposed system architecture

For maintaining high stability and production yield of production equipment in a semiconductor fab, on-line quality monitoring of wafers is required. In current practice, physical metrology is performed only on monitoring wafers that are periodically added in production equipment for processing with production wafers. Hence, equipment performance drift happening in-between the scheduled monitoring cannot be detected promptly. This may cause defects of production wafers and the production cost. In this paper, a novel virtual metrology scheme (VMS) that is based on a radial basis function neural network (RBFN) is proposed for overcoming this problem. The VMS is capable of predicting quality of production wafers using real-time sensor data from production equipment. Consequently, equipment performance abnormality or drift can be detected timely. Finally, the effectiveness of the proposed VMS is validated by tests on chemical vapor deposition (CVD) processes in practical semiconductor manufacturing. It is therefore proved that RBFN can be effectively used to construct prediction models for CVD processes

The required reliability in applications of a distributed computer system is continuous service for 24 hours a day, 7 days a week. However, computer failures due to exhaustion of operating system resources, data corruption, numerical error accumulation, and so on, may interrupt services and cause significant losses. Hence, this work proposes an application cluster service (APCS) scheme. The proposed APCS provides both a failover scheme and a state recovery scheme for failure management. The failover scheme is designed mainly to automatically activate the backup application for replacing the failed application whenever it is sick or down. Meanwhile, the state recovery scheme is intended primarily to provide an inheritable design pattern to support applications with state recovery requirements. An application simply needs to inherit and implement this design pattern, and then can accomplish the task of state backup and recovery. Furthermore, a performance evaluator (PEV) that can detect performance degradation and predict time to failure is developed in this study. By using these detection and prediction capabilities, the APCS can perform the failover process before node breakdown. Thus, applying APCS and PEV can enable a distributed computer system to provide services with near-zero-downtime.

A generic embedded device (GED) that can be installed to various kinds of information equipment, such as manufacturing equipment, portal servers, automatic guided vehicles, etc., is successfully developed In this work. GED is equipped with an embedded real-time operating system and several software modules to retrieve, collect, and manage equipment data. In particular, the communication management module of GED can transmit and receive data to/from remote clients via both wired and wireless networks. Moreover, GED has an object-oriented application interface that flexibly enables GED to add-in or update any customized application. Three typical communication mechanisms, namely the standard processes of exception notification, periodic inspection, and data inquiry are built in GED. As such, GED is able to handle a variety of customized applications, such as monitoring, detection, diagnostics, and prognostics of various kinds of information equipment. We believe that GED possesses the potentiality of information acquisition and transmission so that it can assist all kinds of information equipment to reach the goal of equipment-to-system (E2S) communication and facilitate the maintenance tasks.

Due to the progress of information technologies, traditional information appliances (IAs) further evolve. IAs enter everyone's home with competitive prices, friendly control interfaces, and wireless networks. Accompanied with the increasing variety and functions of IAs, more and more remote controllers are created and this makes the controller an inseparable part to the associated IA. But such many controllers subjected to different IAs make the operation difficult since you have to switch from one controller to another when you want to operate different IAs. Although, there are some configurable controllers on the markets they must be adjusted with the channels of the subjected IAs before use. In this work, the autonomous and generic remote control scheme is proposed to serve as the remote control mechanism between controllers and IAs. This generic remote controller (GRC) can automatically detect a controlled device and dynamically download the context information from the controlled device. As such, users can conveniently control different IAs without prior configuring the GRC. The infrared, IEEE 802.11b wireless LAN, and Java RMI technologies are first utilized to develop the prototype of GRC. Further, we develop another powerful prototype, which utilizes Bluetooth interface with service discovery protocol (SDP), RFComm protocol, and embedded system technology. As such, the infrastructure and feasibility of this scheme are verified We believe, in the near future, the proposed scheme can be evolved into a practical development platform applied in various devices, such as IAs, production machines, medical instruments, etc., so as to improve the quality of human life.

A holonic manufacturing system, designed to realize agile manufacturing, must (be able to) integrate the entire range of manufacturing activities from ordering, through design, modeling, production, to delivery. These activities are performed at many distributed sites. In order to effectively integrate these distributed sites, this work adopts distributed object and mobile object technologies, RosettaNet implementation framework, as well as holon and holarchy concepts derived from studying social organizations and living organisms to develop a holonic information coordination system (HICS). The generic holon is first developed by adopting the technologies of the distributed object-oriented approach with common object request broker architecture infrastructure, n-tier client/server architecture, a knowledge base, and data warehousing to achieve the properties of holon, error recovery, and security certification. The communication holon (CH) is then generated by inheriting the generic holon. Finally, CHs are employed to establish HICS. The CH exhibits basic holonic attributes, such as intelligence, autonomy, and cooperation. Furthermore, the CH can handle partner interface processes, and data exchange by various data formats following the standards of RosettaNet business messages. The failure recovery mechanism of the CH causes HICS to be more reliable than legacy systems. As such, HICS can meet the future requirements of supply-chain information integration of virtual enterprises.Note to Practitioners-An HICS that handles the information flow of the supply chain is proposed in this work. HICS is composed of many communication holons (CHs). Any company that would like to use HICS to exchange information for enterprise integration may possess a CH. The CH is implemented with the Java web-start technology. Therefore, any company can download a CH from the web server via a web browser. The company is, then, able to communicate with other members throughout the supply chain. Accordingly, CHs are scattered throughout the Internet/intranet and each CH can act as both an information supplier and an information consumer. Further, because the CH adopts the RoesettaNet implementation framework (RNIF), any company that has the capability of RNIF can also communicate with the members in the HICS framework via RosettaNet business messages.

With the popularity of PC and the coming of Internet era, more and more software systems are constructed under a distributed object-oriented environment. Software systems constructed with the distributed object-oriented technology have the advantages of openness, modularization, flexibility and easy maintenance. Also, a distributed software system can efficiently solve the problems that need complicated computing. However, testing and debugging in the later stage of software development demand great deal of resources, and open-environment architecture of general distributed systems tends to increase the complexity of testing. To resolve the problems mentioned above, this work proposed a Generic Tester for distributed object-oriented systems. This Generic Tester is applicable to the tests of an individual component or module and even the whole distributed object-oriented system as long as the functions and operations of the components or system can be presented with only class diagrams (as well as interface definitions) and sequence diagrams generated by the tools used during software development. Research results indicate that this Generic Tester enables an integrated planning of software development and testing, reduces testing cost, and improves overall development efficiency.

In recent years, the emerging Web-services technology has provided a new and excellent solution to the data integration among heterogeneous systems. In this paper, a Web-services-based e-diagnostics framework (WSDF) is proposed. It can achieve the automation of diagnostic processes and diagnostics-information integration for semiconductor equipment. First, the system framework and the system component model are designed. Then, the object-oriented analysis and design of system components are accomplished. In particular, for the purpose of code reuse, several common functions, such as SOAP communication, UDDI registration, security mechanism, data exchange mechanism, and local database access, are built into a generic component, called Web-service agent. By inheriting the Web-service agent, other system components can be constructed and have these common functions. In addition, a generic equipment object model, a unified authentication-service mechanism, and a safe network connection are also designed in the framework. WSDF is intended to support the e-diagnostics functions defined by International SEMATECH. It is believed that WSDF can be applied to construct e-diagnostics systems for semiconductor manufacturing industry.

There are hundreds of equipment in a semiconductor factory. In order to increase equipment utilization and improve product quality yield, more reliable services provided by equipment managers are expected. Therefore, it is essential to develop a reliable service management scheme (SMS) for semiconductor factory management systems. In this work, the SMS is developed by applying the Jini and contract technologies. A generic evaluator (GE) is also developed in the SMS to possess error-detection and function-replacement. The GE can also maintain the credit values of all the equipment managers. With the SMS, the process status and parameters of equipment managers in service are stored periodically. If an equipment manager malfunctions, the GE detects and confirms it and sends an event notice to the factory manager. Then, the factory manager finds a spare equipment manager and transfers the backup process status and parameters to the spare equipment manager. Finally, the spare equipment manager can continue monitor the manufacturing process starting from the point where the malfunctioned one left off. Evaluation of reliability improvement and an illustrative example of the SMS are also presented.

In this paper we propose a novel equipment integration framework that is constructed on top of Ethernet and possesses the capability of real-time, synchronous control networks. The equipment integration framework can be used in the equipment-control layer of factory automation networks. Also, it can easily integrate with information-management layer networks. Simulation and experimental results with a laboratory-scale factory show that the proposed equipment integration framework can not only achieve a good performance but also remedy some drawbacks of traditional automaton networks. It is believed that our work can be a significant contribution for factory automation.

A holonic manufacturing system (HMS), which is designed to realize an agile manufacturing enterprise, must be able to integrate the entire range of manufacturing activities from market demands, design, modeling, production, through delivery. These entire activities are implemented by several distributed sites. In order to effectively integrate these distributed sites, we adopt distributed object, mobile object, and object web technologies as well as the holon and holarchy concepts derived from studying social organizations and living organisms to develop a holonic information coordination system (HICS). The generic holon is first developed to achieve the properties of holon, error recovery and security certification. Communication holons are then generated by inheriting generic holon. Finally, communication holons are used to establish HICS. Thus, communication holons have the basic holonic attributes, such as intelligence, autonomy, and cooperation. Further, communication holons can handle information sharing, coordination among enterprises and data exchange by different data format. It is believed that HICS can meet the future requirements of supply chain information integration for virtual enterprises.

In this paper, a novel quantitative measure of redundancy, called refined redundancy index (RRI), which is measured in the joint-rate level, is proposed. Based on the concept that a larger solution space of the inverse kinematics problem represents larger redundancy, the RRI is defined as the normalized magnitude of the solution spaces. The value of the RRI varies from 0 to 1, and larger RRI corresponds to larger redundancy. Unlike joint-angle-level approaches, our method does not have the problem that different regions of joint angles correspond to the same primary task. The proposed RRI is computationally efficient and easy to apply for real-time applications. Simulation results show that with RRI the manipulator can reduce the execution time of a given task significantly, compared to the conventional approach. The results also illustrate that motion failures can be avoided with RRI. It is believed that RRI can be applied to a variety of applications of redundant robots in the future.

Equipment communications is essential for semiconductor manufacturing automation. Equipment managers generally function to communicate between the manufacturing execution system (MES) and equipment. To achieve generality and reusability, our previous work developed a generic equipment manager (GEMG). The rules governing the GEMG were divided into three independent portions: system/framework rules, business rules, and equipment rules. These rules were implemented in the MES interface, controller application (CA), and equipment driver (ED) modules, separately. Among them, equipment rules in the ED modules are equipment-dependent. Connecting a different machine to the GEMG requires modifying the associated ED accordingly, which is a difficult task. To solve this problem, this study proposes a web-enabled equipment driver (WED) that uses mobile object technology. Initially, a mobile object model with a Java applet, namely WED, is developed. WED is constructed on the equipment (server) side. Then, the equipment manager (client) downloads WED via a web browser. This process does not need to modify the ED. Subsequently, the equipment manager can communicate with the equipment by either the Java socket technology using the HSMS standard or the object web technology through the CORBA or DCOM protocols using the OBEM standard. This proposed scheme has been successfully implemented. Illustrative examples reveal that the proposed mobile object model and WED establish a novel, efficient, and versatile scheme for semiconductor equipment communications.

Equipment Managers (EMs) play a major role in a Manufacturing Execution System (MES). They serve as the communication bridge between the components of an MES and the equipment. The purpose of this paper is to propose a novel methodology for developing analytical and simulation models for the EM such that the validity and performance of the EM can be evaluated. Domain knowledge and requirements are collected from a real semiconductor packaging factory. By using IDEFO and state diagrams, a static functional model and a dynamic state model of the EM are built. Next, these two models are translated into a Petri net model. This allows qualitative and quantitative analyses of the system. The EM net model is then expanded into the MES net model. Therefore, the performance of an EM in the MES environment can be evaluated. These evaluation results are good references for design and decision making.

We propose to include the vehicle body sway motion into the motion planning of a quadruped's wave gaits such that its stability margin can be substantially increased. Two sway motions are proposed: Y-sway and E-sway. The Y-sway motion is simple, which drives the center of gravity (CG) of the vehicle to approach to the y-component of the geometric center of the contact points of the supporting legs. The E-sway motion drives CG to approach to the desired CG locus for considering equal energy stability levels. Both sway motions are reasonably easy to implement. Between them, the E-sway can achieve better stability margin. When sloped terrains are encountered, body tilt is also considered in the initialization phase to improve the stability margin. Simulation results show that the body sway motions and tilt consideration are not mutually exclusive. Therefore, we may combine both actions to further increase the stability margin.

Information integration of the supply chain for the manufacturing industry is essential because a competent and promising company needs an efficient information system to communicate with its customers, supplies, and partners within the entire supply chain. In this research, a collaborative and event-driven supply chain information system (SCIS) is developed by using mobile object technology. The Unified Modeling Language (UML) is applied to analyze and design the SCIS Framework which contains two major components: information coordinator component (ICC) and agent component (AC). The ICC acts as the information integration manager. It manages all the ACs and establishes proper event channels for them to exchange information. Each member within the supply chain needs to possess an AC such that it can utilize the SCIS to exchange information with the other members. An application example is constructed and its corresponding system integration and testing procedure is demonstrated. From this demonstration result, it is believed that this SCIS framework provides a collaborative, event-driven, object-oriented, and agent-based infrastructure for the supply chain members to mutually exchange information efficiently.

The force distribution problem in multilegged vehicles is a constrained optimization problem. The solution to the problem is the setpoints of the leg contact forces for a particular system task. In this paper, the efficient compact QP method which takes into account both the linear and quadratic objective functions is adopted to resolve this constrained optimization problem. Various objective functions such as minimum force, load balance, safety margin on friction constraints can be considered by the compact QP method. This method can also be applied to smooth discontinuities in commanded forces by manipulating the homogeneous solution and including smoothing periods when the leg phase alternates between support and transfer. This smoothing scheme does not require force sensors. Multiple goals which consider several alternative objective functions can also be achieved by the compact QP method.

Today, most of the manufacturing execution systems (MES) are large, monolithic, insufficiently configurable and difficult to modify. Using a distributed object-oriented technique, we present a systematic approach to develop a computer-integrated MES framework which is open, modularised, distributed, configurable, interoperable, collaborative, and maintainable. The CORBA infrastructure is adopted to develop this integratable MES. We also use OLE automation and COM objects to construct sample applications. An example is shown to demonstrate the fruit of this systematic approach.

The equipment manager plays one of the major roles in a manufacturing execution system (MES). It is the communication bridge between the components of MES and the equipment. The soul of an equipment manager is its control algorithm. The purpose of this paper is to develop such a control algorithm. The domain knowledge and requirements are collected from a real semiconductor packaging factory. By using the IDEF0 methodology and the system state diagrams, the functional model and the dynamic model of the control algorithm are built. Then, the control algorithm is translated into the Petri-net model. This allows the qualitative and quantitative analysis of the system. The Petri-net model of the equipment manager is included into the MES Petri-net model. As such, the performance of an equipment manager in the MES environment can be evaluated. These evaluation results are good references for design and decision-making. Finally, the proper control algorithm is converted into the application program of the equipment manager.

The window-shaped obstacle avoidance problem is studied in this paper. Several research papers regarding obstacle avoidance including the method proposed by Zghal et al., which we believe is the most suitable for three-dimensional (3-D) window-shaped obstacle avoidance are studied. Consequently, several shortcomings of the Zghal's method are discovered. The Zghal's method will produce chattering solution sequences in joint rates due to its deficiency in determining the shortest distance between the manipulator links and the window edges. This paper proposes a new scheme to determine the shortest distance. This new scheme will remedy the chattering problem. Moreover, the nearest link (NL) method is developed for further improvement. Because the NL method only considers the nearest link in the performance criterion, the on-line weighting assignment problem of the Zghal's method is removed, also, less redundancy is required to accomplish the goal for obstacle avoidance. Therefore, the NL method will allow more redundancy to be useful for the other goals under multiple-goal application environments.

The window-shaped obstacle avoidance problem is studied in this paper. Several research papers regarding obstacle avoidance including the method proposed by Zghal et al. (1992), which we believe is the most suitable for 3D window-shaped obstacle avoidance were studied. Consequently, several short-comings of the Zghal's method were discovered. The Zghal's method will produce a chattering problem due to its deficiency in determining the shortest distance between the manipulator links and the window edges. This paper proposes a new scheme to determine the shortest distance. This new scheme will remedy the chattering problem. Moreover, the most dangerous link (MDL) method is developed to further improve the effectiveness and efficiency. Because the MDL method only considers the most dangerous link in the performance criterion, the online weighting assignment problem of the Zghal's method is removed, also, less redundancy is required to accomplish the goal for obstacle avoidance. Therefore, the MDL method will allow more redundancy to be useful for the other goals under multiple-goal application environments.

The parallel scheme is an effective algorithm to solve the multiple-goal problem of redundant manipulators, but it has limitations. We present an improved parallel scheme to help solve the limitations of the original parallel scheme. The original scheme has problems with the redundancy-release capability. We propose using the exponential function to adaptively adjust the weighting under the improved parallel scheme. The original parallel scheme uses a reciprocal function. Our solution shows both an improved redundancy-release capability and weighting-adjustment capability. Our improved parallel scheme has these advantages plus the original merits of the original parallel scheme.

A compact formulation which is more efficient than the traditional pseudoinverse formulation for obtaining the general solution for the force balance equations has been presented (Cheng and Orin, 1991). With hard point contacts considered, the force balance equations can be decomposed into two sets of rank 3, smaller linear equations if proper coordinate frames of the reference member and at the contact points are chosen. This decomposition, together with the compact formulation, can reduce the steps of the Gaussian elimination process, increase parallelism of the algorithm, and therefore, keep the computation time for obtaining the general solution for the force balance equations to a minimum.

Upon solving the inverse kinematics problem of robot manipulators, the inherent singularity problem should always be considered. When a manipulator is approaching a singular configuration, a certain degree of freedom will be lost such that there are no feasible solutions of the manipulator to move into this singular direction. In this paper, the singularities of a 6-DOF PUMA manipulator are analyzed in detail and all the corresponding singular directions in task space are clearly identified. In order to resolve this singularity problem, an approach denoted Singularity Isolation Plus Compact QP (SICQP) method is proposed. The SICQP method decomposes the work space into achievable and unachievable (i.e., singular) directions. Then, the exactness in the singular directions are released such that extra redundancy is provided to the achievable directions. Finally, the Compact QP method is applied to maintain the exactness in the achievable directions, and to minimize the tracking errors in the singular directions under the condition that feasible joint solutions must be obtained. In the end, some simulation results for PUMA manipulator are given to demonstrate the effectiveness of the SICQP method.

It becomes obvious that a single optimization criterion is not sufficient to deal with complicated task environments when redundant manipulators execute real-world tasks. Therefore, multiple-goal considerations should be considered. In this research, a systematic algorithm, namely the parallel scheme is proposed to solve the multiple-goal problem. It can adaptively adjust all the weighting factors of the corresponding goals according to their individual needs under dynamically varying environments. As such, smooth solution sequences are obtained. The 7-DOF CESAR redundant manipulator is used as an example mechanism to test the proposed algorithms for multiple-goal considerations.

The compact QP method is an effective and efficient algorithm for resolving the manipulator redundancy under inequality constraints. In this paper, a more computationally efficient scheme which will improve the efficiency of the compact QP method-the improved compact BP method-is developed. With the technique of work space decomposition, the redundant inverse kinematics problem can be decomposed into two subproblems. Thus, the size of the redundancy problem can be reduced. For an n degree-of-freedom spatial redundant manipulator, instead of a 6/spl times/n matrix, only a 3/spl times/(n-3) matrix is needed to be manipulated by Gaussian elimination with partial pivoting for selecting the free variables. The simulation results on the CESAR manipulator indicate that the speedup of the compact QP method as compared with the original QP method is about 3.3. Furthermore, the speedup of the improved compact QP method is about 5.6. Therefore, it is believed that the improved compact QP method is one of the most efficient and effective optimization algorithm for resolving the manipulator redundancy under inequality constraints.>

The compact QP method is an effective and efficient algorithm for resolving the manipulator redundancy under inequality constraints. In this paper, a more computationally efficient scheme which will improve the efficiency of the compact QP method-the improved compact QP method -is developed. With the technique of workspace decomposition, the redundant inverse kinematics problem can be decomposed into two subproblems. Thus, the size of the redundancy problem can be reduced. For an n degree-of-freedom spatial redundant manipulator, instead of a 6/spl times/n matrix, only a 3/spl times/(n-3) matrix is needed to be manipulated by Gaussian elimination with partial pivoting for selecting the free variables. The simulation results on the CESAR manipulator indicate that the speedup of the compact QP method as compared with the original QP method is about 4.3. Furthermore, the speedup of the improved compact QP method is about 5.6. Therefore, it is believed that the improved compact QP method is one of the most efficient and effective optimization algorithm for resolving the manipulator redundancy under inequality constraints.>

Due to hardware limitations, physical constraints such as joint rate bounds, joint angle limits, and joint torque constraints always exist. In this paper, these constraints are considered in the general formulation of the redundant inverse kinematic problem. To take these physical constraints into account, the computationally efficient compact quadratic programming (QP) method is formed to resolve the constrained kinematic redundancy problem. In addition, the compact-inverse QP method is also formulated to remedy the inescapable singularity problem with inequality constraints. Two examples are given to demonstrate the generality and superiority of these two methods: to eliminate the drift phenomenon caused by self motion and to remedy saturation-type nonlinearity problems.>

Due to hardware limitations, physical constraints, such as joint rate bounds and joint angle limits, always exist. In the present work, these constraints are included in the general formulation of the redundant inverse kinematic problem. To take into account these physical constraints, the computationally efficient compact QP (quadratic programming) method is derived to resolve the kinematic redundancy problem. In addition, the compact-inverse QP method is developed to remedy the singularity problem. The compact QP (compact and inverse QP) method makes use of the compact formulation to obtain the general solutions and to eliminate the equality constraints. As such, the variables are decomposed into basic and free variables, and the basic variables are expressed by the free variables. Thus, the problem size is reduced and it only requires an optimization algorithm, such as QP, for the free variables subject to pure inequality constraints. This approach will expedite the optimization process and make real-time implementation possible.>

The inverse kinematic problem of redundant manipulators is solved by the compact formulation technique. The compact formulation is derived by applying Gaussian elimination, then the general solutions are still formulated as a particular solution together with homogeneous solutions. The homogeneous solutions are merely functions of free variables. Inverse kinematic solutions derived by the pseudoinverse formulation can always be converted into a compact form. Also, it is proven that the implementation by the compact formulation is computationally more efficient. The inherent singularity problems of inverse kinematics are also considered. In order to obtain continuous and feasible joint-rate solutions even at or in the neighborhood of singular points and to improve the exactness in the achievable directions, the compact-inverse method is introduced. The compact-inverse method applies the compact formulation to constrain the manipulator to move into the achievable directions. It is believed that the compact formulation approach can resolve the inverse kinematic redundancy problem more efficiently and exactly than the traditional pseudoinverse formulation.>

The force-distribution problem in multiple-chain robotic systems is to solve for the setpoints of the chain contact forces and input joint torques for a particular system task. It is usually underspecified, and an optimal solution may be obtained. The generality of the compact-dual linear programming (LP) method that can accept a variety of linear objective functions for different applications over a wide range of multiple-chain systems (multilegged vehicles, dexterous hands, and multiple manipulators) is demonstrated; and the solutions for several common problems of force distribution including slippage avoidance, minimum effort, load balance, and temporal continuity are proposed. This is illustrated by solving the force-distribution problem of a grasping system being developed called Digits. Efficiency considerations and elimination of redundant constraints are also discussed. With four fingers grasping an object, considering a conservative friction coefficient (for safety margins on friction constraints) and using a combined objective function for achieving the goals of minimum effort, load balance, and temporal continuity, the CPU time on a VAX-11/785 computer is less than 45 ms (using a linear programming package in the IMSL library). Therefore, it is believed that rather general use of the compact-dual LP method may be made to define a suitable objective function for a particular application and to solve the corresponding force-distribution problem in real time.>

Force distribution is the inverse dynamics problem for multiple-chain systems in which the motion is completely specified and the internal forces/torques to effect this motion are to be determined. A computationally efficient formulation for the force-distribution problem is presented. This formulation is applicable to a number of simple closed-chain robotic mechanisms, including dexterous hands, multiple manipulators, and multilegged vehicles. Modeling of chain contacts is relatively general so that hard point contact, soft finger contact or rigid contact with an irregularly-shaped object or with uneven terrain may be handled. The dynamic effects of the chains and physical limits on their actuators are efficiently included in the formulation through the use of the inverse dynamics and Jacobian relationships for each chain. Based on this efficient formulation, a variety of methods may then be developed to solve the force-distribution problem.>

An efficient algorithm, the compact-dual linear programming (LP) method, is presented to solve the force distribution problem. In this method, the general solution of the linear equality constraints is obtained by transforming the underspecified matrix into row-reduced echelon form; then, the linear equality constraints of the force distribution problem are eliminated. In addition, the duality theory of linear programming is applied. The resulting method is applicable to a wide range of systems, constraints, and objective functions and yet is computationally efficient. The significance of this method is demonstrated by solving the force distribution problem of a grasping system under development at Ohio State called DIGITS. With two fingers grasping an object and hard point contact with friction considered, the CPU time on a VAX-11/785 computer is only 1.47 ms. If four fingers are considered and a linear programming package in the IMSL library is utilized, the CPU time is then less than 45 ms.>

The authors present a general and efficient algorithm, the compact-dual LP method, to solve the force distribution problem for multiple-chain robotic systems. In this method, the general solution of the linear equality constraints is obtained by transforming the underspecified matrix into row-reduced echelon form; then the linear equality constraints of the force distribution problem are eliminated. The duality theory of linear programming is also applied. The resulting method is applicable to a wide range of systems, constraints (friction constraints, joint torque constraints, etc.), and objective functions and yet is computationally efficient. The significance of this method is demonstrated by solving the force distribution problem for a grasping system. For an example involving two-finger grasping of an object and hard point contact with friction, the CPU time on a VAX-11/785 computer is only 1.47 ms. If four fingers are considered, then the CPU time is less than 45 ms, which should be suitable for real-time application.>