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

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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.

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

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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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

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

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

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

A previously developed pneumatic muscles’ (PMs) actuated gait exoskeleton (with only knee joint) has been demonstrated in achieving appropriate actuation torque, range of motion (ROM), and control bandwidth for task-specific gait training. While the adopted multi-input–multi-output (MIMO) sliding mode (SM) strategy has preliminarily implemented simultaneous control of the exoskeleton’s angular trajectory

Fault location algorithms for transmission lines use the parameters of the transmission line to locate faults after the faults have occurred along the line. Although these parameters can be estimated by the phasor measurement units (PMUs) at the terminal(s) of the transmission line continuously, the uncertainty in the measurements will give rise to stochastic errors in the measured values. Thus, the

The treatment of malaria is a global health challenge that stands to benefit from the widespread introduction of a vaccine for the disease. A method has been developed to create a live organism vaccine using the sporozoites (SPZ) of the parasite Plasmodium falciparum (Pf), which are concentrated in the salivary glands of infected mosquitoes. Current manual dissection methods to obtain these PfSPZ are

This article proposes a two-finger-based micrograsping system with high compliant borosilicate 3.3 glass probes and the corresponding sensing and control algorithms, which enables the orientation manipulation of microparts in three-dimensional (3-D) space. Compared with the existing research, the novelty of this article relies on three aspects: 1) the end-effector of the microgripper is designed to

Precise 3-D surface reconstruction plays an important role in automated manipulation, industrial inspection, robotics, and so on. In this article, we present a novel 3-D surface reconstruction framework for stereo vision systems assisted with structured light projection. In the framework, a multistep matching scheme is proposed to establish a reliable correspondence between image pairs with high computation

This article considers the problem of assigning mobile robots to goals on transport networks with uncertain and potentially correlated information about travel times. Our aim is to produce optimal assignments such that the average waiting time at destinations is minimized. Since noisy travel time estimates result in suboptimal assignments, we propose a method that offers robustness to uncertainty by

Metadata in most existing building automation systems (BASs) is inconsistent, incomplete, and nondescriptive. This situation is a major obstacle to the widespread use of data analytics to improve the operation of buildings. In this article, we put forward a method to infer zone-level metadata from features derived from BAS data. The method includes two steps: 1) classification of BAS points into different

In the machine learning domain, active learning is an iterative data selection algorithm for maximizing information acquisition and improving model performance with limited training samples. It is very useful, especially for industrial applications where training samples are expensive, time-consuming, or difficult to obtain. Existing methods mainly focus on active learning for classification, and a

Nowadays, the entire world is facing challenges in energy and environment. To resolve these problems, the power systems are interconnected to promote the development of renewable energy sources (RESs). However, the economic dispatch (ED) problem for the global energy interconnection (GEI) should tackle two issues: 1) handle the uncertainty from RES and allocate the responsibility among the interconnected

Ambient assisted living and smart home technologies are a good way to take care of dependent people whose number will increase in the future. They allow the discovery and the recognition of human’s activities of daily living (ADLs) in order to take care of people by keeping them in their home. In order to consider the human behavior nondeterminism, probabilistic approaches are used despite difficulties

The optical tracking system (OTS) plays a vital role in the computer-assisted surgical navigation process, whereas the performance of the commonly used binocular stereo vision is affected by the line-of-sight problem and limited workspace. Thus, this article proposed a prior knowledge-based multicamera reconstruction model (PKRM) to both expand the tracking workspace and improve the tracking robust

Somatic cell nuclear transfer (SCNT), which is an important procedure in cloning, has been conducted manually for decades. The operating efficiency drops sharply in batch SCNT because of the long-time observation under microscopy and the time-wasting traditional process. Though the operating time was reduced by robotic SCNT in previous studies, the traditional operating process was still used. In this

The development of autonomous or semiautonomous surgical robots stands to improve the performance of existing teleoperated equipment but requires fine hand-eye calibration between the free-moving endoscopic camera and patient-side manipulator arms (PSMs). A novel method of solving this problem for the da Vinci robotic surgical system and kinematically similar systems is presented. First, a series of

Deadlock resolution has been an important research topic in the field of automated manufacturing systems (AMSs). Researchers generally assume that AMS resources never break down whereas only a few resolve the issues of resource failures in the discrete-event supervision of AMSs. In fact, an AMS consists of a number of numerically controlled machines interacting with each other. The failure of resources

In a human–robot coexisting environment, it is pivotal for a mobile service robot to arrive at the goal position safely and efficiently. In this article, an elastic band-based rapidly exploring random tree (EB-RRT) algorithm is proposed to achieve real-time optimal motion planning for the mobile robot in the dynamic environment, which can maintain a homotopy optimal trajectory based on current heuristic

This article studies a steelmaking–continuous casting (SCC) scheduling problem by considering ladle allocation. It takes technological rules in steel manufacturing and ladle-related constraints into account. A scheduling problem is formulated to determine allocation equipment for jobs, production sequence for jobs processed by the same equipment, and modification operations for empty ladles after their

In the reverse Stackelberg mechanism, by considering a decision function for the leader rather than a decision value in the conventional Stackelberg game, the leader can explore a wider decision space. This flexibility can result in realizing the globally optimal solution of the leader’s objective function, while controlling the reaction function of the followers, simultaneously. We consider an aggregator

Fault prognosis of the air-handling systems, which are the key subsystems of heating, ventilation, and air conditioning systems, allows system operators to know the remaining useful life (RUL), thus preventing unexpected breakdowns and reducing the operational and maintenance costs. In this article, a new hidden semi-Markov model-based method is developed. In the method, only relevant state-transition

Smart customization service is an important element for smart manufacturing. The success of smart customization requires that designers, manufacturers, and customers with differences in context, semantics, and other cognitive aspects be engaged in a collaborative process. With product configurators reported to have positive impacts on product quality to meet customers’ needs, this article attempts

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The steelmaking process in the iron and steel industry involves complicated physicochemical reactions. The main aim of steelmaking is to adjust the quality of molten steel. During the steel-tapping process, the temperature and carbon content are the most essential quality indices for end-point prediction. This article presents a novel machine learning framework for the end-point prediction problems

In this article, we introduce a translational force control method with disturbance observer (DOB)-based force disturbance cancellation for precise 3-D acceleration control of a multi-rotor unmanned aerial vehicle (UAV). The acceleration control of the multi-rotor requires conversion of the desired acceleration signal to the desired roll, pitch, and total thrust. However, because the attitude dynamics

Automatic polyp recognition in endoscopic images is challenging because of the low contrast between polyps and the surrounding area, the fuzzy and irregular polyp borders, and varying imaging light conditions. In this article, we propose a novel densely connected convolutional network with “unbalanced discriminant (UD)” loss and “category sensitive (CS)” loss (DenseNet-UDCS) for the task. We first

A significant challenge in comprehensive geometric accuracy control of an additive manufacturing (AM) system is the specification of shape deviation models for different computer-aided design products manufactured on its constituent AM processes. Current deviation modeling techniques do not satisfactorily address this challenge because they can require substantial user inputs and efforts to implement

We present a method for fabricating general models with multi-directional 3-D printing systems by printing different model regions along with different directions. The core of our method is a support-effective volume decomposition algorithm that minimizes the area of the regions with large overhangs. A beam-guided searching algorithm with manufacturing constraints determines the optimal volume decomposition

In this article, we propose an augmented reality semiautomatic labeling (ARS), a semiautomatic method which leverages on moving a 2-D camera by means of a robot, proving precise camera tracking, and an augmented reality pen (ARP) to define initial object bounding box, to create large labeled data sets with minimal human intervention. By removing the burden of generating annotated data from humans,

Considering time-varying transition probability (TVTP), this article combines Markov regime switching with a dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model to construct a new hedging model and study a state-dependent minimum variance hedging ratio. A two-stage maximum likelihood method is constructed to estimate the model parameters. A filtering

Pulp is the most important raw material in paper industries, whose fiber length stochastic distribution (FLSD) shaping directly determines the energy consumption and paper quality of the subsequent papermaking processes. However, the mean and variance are insufficient to describe the FLSD shaping, which displays non-Gaussian distributional properties. Therefore, the traditional control method based