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To Perform reliably and consistently over sustained periods of time, large-scale automation critically relies on computer simulation. Simulation allows us and supervisory AI to effectively design, validate, and continuously improve complex processes, and helps practitioners to gain insight into the operation and justify future investments. While numerous successful applications of simulation in industry

Advancement in healthcare solutions is one of the major success stories of our times. While biomedical science and engineering has progressed significantly, increased human longevity has created huge demands on the healthcare system, such as the workforce that is struggling to meet the needs of patients. With the advent of healthcare automation, doctor offices, hospitals, and other medical facilities

Learning from subject’s calibration data can significantly improve the performance of a steady-state visually evoked potential (SSVEP)-based brain–computer interface (BCI), for example, the state-of-the-art target recognition methods utilize the learned subject-specific and stimulus-specific model parameters. Unfortunately, when dealing with new stimuli or new subjects, new calibration data must be

Energy places an important role in a new scale of urbanization, digitization, and industrialization. Going “energy-efficient” then becomes a major component of the missions for manufacturers and service providers to stay globally competitive. In recent years, the newly emerging intelligent technologies are enhancing the production process and control management in an energy-effective and -efficient

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The hand gesture recognition system is a noncontact and intuitive communication approach, which, in turn, allows for natural and efficient interaction. This work focuses on developing a novel and robust gesture recognition system, which is insensitive to environmental illumination and background variation. In the field of gesture recognition, standard vision sensors, such as CMOS cameras, are widely

Smart manufacturing is targeted as the next generation of manufacturing by many national and international strategic development. The increasingly rich production data, the integration and extensive application of information technology, and the intelligent data processing and system modeling methods have collectively enabled smart manufacturing. Building upon them, manufacturing system modeling, knowledge

The 15th annual IEEE International Conference on Automation Science and Engineering (CASE 2019) was held on August 22–26, 2019, at The University of British Columbia, Vancouver, BC, Canada. IEEE CASE represents the flagship automation conference of the IEEE Robotics and Automation Society and constitutes the primary forum for cross-industry and multidisciplinary research in automation. Its goal is

Home care (HC) services represent an effective solution to face the health issues related to population aging. However, several scheduling problems arise in HC, and the providers must make several scheduling and routing decisions, e.g., the assignment of caregivers to clients, in order to balance operating costs and client satisfaction. Starting from the analysis of a real HC provider operating in

Tool-center-point (TCP) control increases the operating comfort of concrete pumps by shifting the control to the task space. The operation is accompanied by various requirements and constraints from the mechanical structure, the hydraulic system, and the operator. They must be taken into account for the efficient and error-free operation of the concrete pump. In this publication, a TCP control algorithm

Learning manipulation skills from open surgery provides more flexible access to the organ targets in the abdomen cavity and this could make the surgical robot working in a highly intelligent and friendly manner. Teaching by demonstration (TbD) is capable of transferring the manipulation skills from human to humanoid robots by employing active learning of multiple demonstrated tasks. This work aims

Energy-efficient machining has become imperative for energy conservation, emission reduction, and cost saving of manufacturing sectors. Optimal machining parameter decision is regarded as an effective way to achieve energy efficient turning. For flexible machining, it is of utmost importance to determine the optimal parameters adaptive to various machines, workpieces, and tools. However, very little

Machine state control is one of the most promising energy-efficient measures for machining processes. A proper control reduces the energy consumed during idle periods by switching off/on the machines. A critical barrier for practical implementation is related to the knowledge of part arrival process that is affected by uncertainty. The stochastic processes involved in the system are usually assumed

In recent years, lower limb exoskeletons have gained considerable interest in applications of walking assistance for paraplegic patients. In daily lives, the exoskeleton should have the ability to help the patients to walk over different terrains. For sloped terrains, how to plan the stepping locations on slopes with different gradients and generate stable human-like gaits for patients is a critical

A little volume of lower extremity amputees needs hip disarticulation prostheses (HDPs). This situation makes it hard to invite hip amputees for prostheses test. The traditional evaluations for HDPs mostly refer to the questionnaires from the amputees and lack of quantitative criteria. In this article, we proposed a gait simulation and evaluation (GSE) system for HDPs testing. The GSE system contained

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In recent decades, there has been an increasing interest in the use of robotic powered exoskeletons to assist patients with movement disorders in rehabilitation and daily life. Providing assistive torque that compensates for the user’s remaining muscle contributions is a growing and challenging field within exoskeleton control. In this article, ankle joint torques were estimated using electromyography

Gesture recognition becomes a thriving research area in modern human motion recognition systems. The intensification of demands on efficient interactive human–machine-interface systems, commercial objectives, and many other factors contributes to fuel this revival dynamics. Understanding human gestures becomes essential for prevention and health monitoring applications. In particular, analyzing hand

Understanding the effects of different hip assistance modes is a fundamental step in the process of designing hip assistance devices and controllers that can provide better performance in terms of metabolic cost. We have developed and tested a soft exoskeleton for hip assistance, which includes three assistance modes: hip extension assistance (HEA), hip flexion assistance (HFA), and hip extension and

Compared with the rapidly growing artificial intelligence (AI) research in other branches of healthcare, the pace of developing AI capacities in dental care is relatively slow. Dental care automation, especially the automated capability for dental cone beam computed tomography (CBCT) segmentation and lesion detection, is highly needed. CBCT is an important imaging modality that is experiencing ever-growing

For practical mechanical systems, uncertainties/disturbances, such as unmodeled dynamics and frictions, are nonignorable factors. For existing control methods, these factors are usually neglected or addressed by a robust way. As a consequence, the nominal control performance of these methods is sacrificed. Moreover, there exists the chattering problem for some existing robust methods, such as sliding

Dissimilarity analysis (DISSIM) has been widely used to monitor the Gaussian processes. However, its further application is hindered due to its unavailability to non-Gaussian processes whose data do not satisfy the hypothesis of the Gaussian distributions. To sensitively detect faults and enhance understanding of the non-Gaussian processes, a Gaussian feature analytics-based DISSIM (GDISSIM) method

The IEEE Transactions on Automation Science and Engineering (T-ASE) wishes to thank the 1110 reviewers over the past year who have performed an essential role in maintaining the quality of this publication. T-ASE strives for the 90-90 standard, i.e., 90% of articles should be reviewed within 90 days of submission. The review process starts when the Editor-in-Chief assigns the paper to an Editor, who

The current trends in personalized products drive the paradigms of production systems toward autonomous networked manufacturing systems. This article proposes an ontology-based holonic event-driven architecture for implementing loosely coupled, holonic, autonomous distributed systems. The event-driven architecture (EDA) enables the services provided by different organizations and their suborganizations

Bin packing and bin covering are important optimization problems in many industrial fields, such as packaging, recycling, and food processing. The problem concerns a set of items, each with its own value, that are to be sorted into bins in such a way that the total value of each bin, as measured by the sum of its item values, is not above (for packing) or below (for covering) a given target value.

Classification of electroencephalogram-based motor imagery (MI-EEG) tasks raises a big challenge in the design and development of brain–computer interfaces (BCIs). In view of the characteristics of nonstationarity, time-variability, and individual diversity of EEG signals, a deep learning framework termed SSD-SE-convolutional neural network (CNN) is proposed for MI-EEG classification. The framework

Among the characteristic symptoms of schizophrenia, negative symptoms are a category. The existence of negative symptoms results in a diminution of normal behaviors and functions for schizophrenic patients. In this research, we focus on the affective flattening of negative symptoms to explore potential biomarkers to achieve automatic diagnosis. This work proposes an automatic procedure for detecting

Sensor scheduling for energy-efficient collaborative target tracking in wireless sensor networks (WSNs) is an important problem to deal with the limited network resources. With the recent development and emerging applications of energy acquisition technologies, it has become possible to overcome the bottleneck of battery energy in WSNs using the energy harvesting devices, where theoretically the lifetime

Industry 4.0 production systems must support flexibility in various dimensions, such as for the products to be produced, for the production processes to be applied, and for the available machinery. In this article, we present a novel approach to design and control smart manufacturing systems. The approach is reactive, that is responds to unplanned situations and implements an iterative refinement technique

This article addresses a real-world tactical production planning problem in which a series of real-world constraints need to be considered, such as no backorder, products with multilevel bills of material (BOMs), and lot streaming production. Under the premise of no backorder, the objective of this plan is to make the workload as balanced as possible throughout the planning horizon. An integer quadratic

Maximum dorsiflexion (MDF) is an important gait event corresponding to the maximum ankle dorsiflexion angle in each gait cycle. MDF timing plays an important role in the control of robotic prosthesis. This article puts forward an on-board adaptive algorithm to detect MDF timing of robotic transtibial prosthesis in different walking conditions (at different speeds and on different ramps) and for different

An improved method for solving conflict-free scheduling and routing of automated guided vehicles is proposed in this article, with promising results. This is achieved by reformulating the mathematical model of the problem, including several improvements and speedup strategies of an existing Benders decomposition method. A new heuristic is also presented that quickly yields high-quality solutions. Moreover

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)

Energy submetering at the equipment level provides a tool to identify energy use anomalies and detect operational inefficiencies. While physical meters can be costly and difficult to install, virtual meters (VMs) overcome practical issues associated with physical meters and provide insights into critical unmeasured quantities. This article introduces an inverse greybox model-based virtual metering

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We are very pleased to present this Special Section of these Transactions, including six extended articles selected from the technical program of the 2017 International Conference on Automation Science and Engineering (CASE 2017), held in Xi’an, China, August 20–23, 2017. CASE is an offspring of the Transactions on Automation Science and Engineering and is the flagship automation conference of the

The 14th Annual IEEE International Conference on Automation Science and Engineering (CASE 2018) sponsored by the IEEE Robotics and Automation Society (RAS) was held on August 20–24, 2018, in Munich, Germany. IEEE CASE is the flagship automation conference of the IEEE RAS and constitutes the primary forum for cross-industry and multidisciplinary research in automation. Its goal was to provide a broad

Cyber–physical systems (CPSs) in the manufacturing domain can be deployed to support monitoring and analysis of production systems of a factory in order to improve, support, or automate processes, such as maintenance or scheduling. When a network of CPS is subject to frequent changes, the semantic interoperability between the CPSs is of special interest in order to avoid manual, tedious, and error-prone

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The nematode worm Caenorhabditis elegans is a model organism widely used in biological research on genetics, development, neuroscience, and aging. Microinjection is an effective and widely adopted method to create transgenetic worms, perform ribonucleic acid (RNA) interference of certain genes, and introduce different types of molecules into specific locations inside a worm body. Based on microfluidics

Large-scale additive manufacturing (LSAM) has a similar mechanism to the fused filament fabrication (FFF) and is capable of fabricating a part in large size. This capability provides LSAM with potentials in a variety of industries, including aerospace and automotive manufacturing. Product quality and production efficiency are two main concerns, as LSAM is implemented. It has been proven that print

This article analyzes the backward sequence for single-armed cluster tools with processing time variations. The backward sequence is popularly used to operate a single-armed cluster tool in practice, but its performance has not been analyzed when processing time variations are introduced. To address the problem, we first define a fundamental cycle and derive a formula for cycle time analysis considering

Ancillary services are becoming an indispensable tool for maintaining power grid stability due to the increasing adoption of renewable energy resources, many of which (e.g., wind and solar power) are inherently variable. Some energy resources, such as electric vehicles (EVs), have a significant potential for providing their own ancillary services and creating ancillary service markets in smart electric

Fault detection, diagnostics, and prognostics (FDD&P) ensure the operation efficiency and safety of engineering systems. In the building domain, they can help significantly reduce energy consumption and improve occupant comfort. Specifically, prognostics are becoming increasingly important as a pro-active fault prevention strategy through continuously monitoring the health of energy systems. In this

Registration is an essential problem in image-guided surgery (IGS) since it brings different involved coordinate frames together. Nonrigid or deformable registration still faces many challenges, such as two point sets (PSs) are partially overlapped. To tackle the challenges in the nonrigid registration, we introduce a new two-step point-based registration pipeline that includes two steps. In the first

Industrial products’ reuse, recovery, and recycling are very important due to the exhaustion of ecological resources. Effective product disassembly planning methods can improve the recovery efficiency and reduce harmful impact on the environment. However, the existing approaches pay little attention to disassembly resources, such as tools and operators that can significantly influence the optimal disassembly

Design optimization of complex engineering problems often involves multiple disciplines or subsystems that usually exist couplings or data interactions with each other. Multidisciplinary design optimization (MDO) is an advanced methodology to deal with such problems. Besides, uncertainty is a crucial factor affecting the performance of complex systems. Therefore, uncertain MDO (UMDO) is the focus of

The idea of using wind power to charge electric vehicles (EVs) has attracted more and more attention nowadays due to the potential in significantly reducing air pollution. However, this problem is challenging on account of the uncertainty in the wind power generation and the charging demand from the EVs. Simulation-based policy improvement (SBPI) has been an important method for decision-making in

E-consults offer a digital platform where primary care physicians (PCPs) can consult specialists and obtain feedback or offer a direct specialty referral to their patients. The goal of this work is to investigate whether e-consults can advance the primary-specialty care interface and reduce referral delays. We provide a high-level abstraction of e-consult operations using an analytical framework that

Demanufacturing aims to recover value and conserve energy from end-of-life (EOL) products, contributing to sustainable manufacturing. To make the full use of EOL products, they are usually disassembled into components that have different values and embodied energy at different EOL options. This article studies a disassembly planning (DP) that integrates the decisions on disassembly sequence and EOL