Supervisory Control and Rehabilitation. Are there Common Interests?

This study focused on identifying recommendations for designing the Next Generation In-Situ Resource Utilization (ISRU) Pilot Excavator (IPEx) control room and facility. This research highlights opportunities for incremental improvements across the control room's design, processes, and amenities, fostering a more efficient and supportive environment for the IPEx team. Participants consisted of IPEx control room operators who were recruited and interviewed; this resulted in 50 recommendations from the 33 open-ended questions asked of the eight participants. Spradley's domain analysis was used to code and analyze the open-ended question responses within 11 domains consisting of design considerations for IPEx displays, room layout, individual desk layout, lighting, shiftwork, shift changeover, control room employee interaction, control room environment, workload, rest area and breaks, and food area. Researchers employed an interview methodology. Spradley’s domain analysis was used to identify and further partition themes into sections called “Cover Terms.” These terms, or themes, were organized further into sub-themes called “Included Terms” for each of the 11 domains. The study implications and future research are also addressed.

Supervisory control of safety-critical systems is usually accomplished by a combination of automation and human authority. Especially in critical situations it is important that the human operator perceives relevant information fast and correctly to ensure safety of the entire system. The abilities of the human perceptual system are limited and thus, Human-Machine Interface (HMI) design should be based on the strengths of human perception. It is crucial to identify how information related to the supervisory control task can be visualized in a way that it can be perceived as fast and as accurate as possible. The current state-of-the-art to design an HMI involves the application of Human Factors (HF) methods to derive the information and the structure necessary for accomplishing the supervisory control task effectively. However, these methods do not offer a systematic approach to further derive an actual visualization that meets human cognitive abilities. This paper presents Konect, a step-by-step method which supports HMI designers to systematically derive psychologically well-founded information visualizations on the basis of well-established HF methods. For a first evaluation of Konect, five HF experts applied the method in a workshop in the automotive domain and approved it. The resulting HMI designs were evaluated against HMIs created by HF experts without Konect in a lab study with 33 participants. Results show that the participants using the Konect HMIs perceived the displayed information significantly faster and more correct than the control group.

In supervisory control and data acquisition (SCADA) systems or the Internet of Things (IoT), human machine interface (HMI) performs the function of data acquisition and control, providing the operators with a view of the whole plant and access to monitoring and interacting with the system. The compromise of HMI will result in lost of view (LoV), which means the state of the whole system is invisible to operators. The worst case is that adversaries can manipulate control commands through HMI to damage the physical plant. HMI often relies on poorly understood proprietary protocols, which are time-sensitive, and usually keeps a persistent connection for hours even days. All these factors together make the vulnerability mining of HMI a tough job. In this paper, we present EUFuzzer, a novel fuzzing tool to assist testers in HMI vulnerability discovery. EUFuzzer first identifies packet fields of the specific protocol and classifies all fields into four types, then using a relatively high efficiency fuzzing method to test HMI. The experimental results show that EUFuzzer is capable of identifying packet fields and revealing bugs. EUFuzzer also successfully triggers flaws of actual proprietary SCADA protocol implementation on HMI, which the SCADA software vendor has confirmed that four were zero-day vulnerabilities and has taken measures to patch up.

Material handling systems, as an important part of different type of manufacturing processes, face the same challenges as manufacturing industries pushed nowadays forward by innovative ideas and technologies to the next level loudly announced as industry 4.0. Development of the next generation of automated manufacturing systems involves advanced approaches to material handling systems design and their close integration with the higher levels of manufacturing and production control and management, e.g. manufacturing execution systems (MES), enterprise resource planning (ERP). In the presence of increasing demands for manufacturing process optimization, the role of supervisory level of material handling systems is much more advanced today, ensuring not only data acquisition, visualization, monitoring, supervisory control, as well as synchronization with the higher control levels (FEM, ERP), but also providing functionality for supporting maintenance and decision-making processes to reduce downtimes, operations and maintenance costs. The article deals with the integration of control and maintenance functions in the hierarchical control system of a crane. The supervisory system for supporting control and proactive maintenance is prototyped at the laboratory overhead travelling crane. The article presents the control-measurement equipment and intelligent software tools implemented in the supervisory control and data acquisition (SCADA) system to aid decision-making process in proactive maintenance. The overview of the main components of the supervisory control and proactive maintenance subsystems is provided, and their respective role in control, supervision, and proactive maintenance is explained. The crane’s supervisory control includes the stereovision-based subsystem applied to identify the crane’s transportation workspace, determine the safety and time-optimal point-to-point trajectory of a payload. The proactive maintenance module consists of the human machine interface (HMI) supporting decision-making process, intelligent tools for upcoming downtime/failure prediction, and the crane's girder inspection using the metal magnetic memory technique.

The improvement of Human-Machine Interface (HMI) design for control rooms on nuclear power plants (NPP) has been accomplished world wide, especially after the TMI-2 accident. The design process and guidelines are standardized in IEC60964 and supplemental standards as international standard. However, technological update is required due to the increased use of computerized control and monitoring equipment and systems in control rooms on NPP in recent years. Standards are becoming more important for computerized control rooms because there is more freedom to design than conventional hardware based system. For computerized control rooms, standards for hardware and software of HMI systems should be also considered. Standards and guidelines for computerized control rooms on NPP have been developed recently in each body such as IEC, ISO, and IEEE etc. Therefore, reviewing these standards and guidelines related to control rooms design of NPP can be useful not only for revision of the international standards such as IEC60964, but also for users of the standards and guidelines. In this paper, we reviewed the international standards related to the design for control rooms, in the two aspects of HMI design and hardware and software design, considering the undergoing revision work and their application.

A supervisory enhanced genetic algorithm control (SEGAC) system is proposed for an indirect field-oriented induction motor (IM) drive to track periodic commands. The proposed control scheme comprises an enhanced genetic algorithm control (EGAC) and a supervisory control. In the EGAC design, the spirit of gradient descent training is embedded in genetic algorithm (GA) to construct the major controller for searching optimum control effort under the possible occurrence of uncertainties. To stabilize the system states around a defined bound region, a supervisory controller, which is derived in the sense of Lyapunov stability theorem, is designed within the EGAC. The effectiveness of the proposed control strategy is verified by numerical simulation and experimental results, and its advantages are indicated in comparison with a conventional supervisory genetic algorithm control (SGAC) system in the previous works.

As nuclear power plants undertake main control room modernization, a challenge is the lack of a clearly defined human factors process to follow. Verification and validation (V&V) as applied in the nuclear power community has tended to involve efforts such as integrated system validation, which comes at the tail end of the design stage. To fill in guidance gaps and create a step-by-step process for control room modernization, we have developed the Guideline for Operational Nuclear Usability and Knowledge Elicitation (GONUKE). This approach builds on best practices in the software industry, which prescribe an iterative user-centered approach featuring multiple cycles of design and evaluation. Nuclear regulatory guidance for control room design emphasizes summative evaluation—which occurs after the design is complete. In the GONUKE approach, evaluation is also performed at the formative stage of design—early in the design cycle using mockups and prototypes for evaluation. The evaluation may involve expert review (e.g., software heuristic evaluation at the formative stage and design verification against human factors standards like NUREG-0700 at the summative stage). The evaluation may also involve user testing (e.g., usability testing at the formative stage and integrated system validation at the summative stage). An additional, often overlooked component of evaluation is knowledge elicitation, which captures operator insights into the system. In this report we outline these evaluation types across design phases that support the overall modernization process. The objective is to provide industry-suitable guidance for steps to be taken in support of the design and evaluation of a new human-machine interface (HMI) in the control room. We suggest the value of early-stage V&V and highlight how this early-stage V&V can help improve the design process for control room modernization. We argue that there is a need to overcome two shortcomings of V&V in current practice—the propensity for late-stage V&V and the use of increasingly complex psychological assessment measures for V&V.

The signed real measure of regular languages has been introduced and validated in recent literature for quantitative analysis and synthesis of discrete-event supervisory (DES) control systems, where all events are assumed to be observable. This paper presents a modification of the language measure for supervisory control under partial observation and shows how to generalize the analysis when some of the events may not be observable at the supervisory level. Thus, for synthesis of DES control systems, the language measure of partially observable discrete-event processes is expressed in a closed form, which is structurally similar to that of completely observable discrete-event processes.

Social Media platforms are increasing user engagements with their attractive User Interfaces (UI) design playing a crucial role in maintaining user involvement. Use of Emotional Intelligence (EI) into the UI transforming user interaction and engagement pattern significantly. With an emphasis on how design decisions affect user behaviour, this study explores the nuanced function of EIUIs (Emotionally Inteligence User Interfaces) in the context of social media. It specifically draws attention to the dangers of manipulative techniques like "dark patterns"-purposeful interface strategies intended to influence users to take actions they might not have otherwise taken-as well as the possibility of constructive involvement. By investigating these practices, the paper hopes to clarify the wider ethical consequences of interface design as well as the duty of platforms and designers to promote transparency, autonomy, and confidence in digital interactions. This paper aims to contribute to the discourse on user interface design by providing a comprehensive understanding of EIUIs' potential and pitfalls in the context of social media interactions. Additionally, this study focusses on finding information of the pattern of Emotionally Intelligent User Interfaces (EIUI) design to enhance user engagements emotionally and tend to take decisions and the impact of the design pattern in user experience.

* Part I: Human performance * Chapter 1: Human error * Chapter 2: Memory and complex skills * Chapter 3: Vigilance * Chapter 4: Situation awareness * Chapter 5: Team working * Part II: Memory and complex skills * Chapter 6: Training for control room tasks * Chapter 7: Humans and machines: Allocation of function * Chapter 8: Tasks analysis * Chapter 9: Training and technology for teams * Chapter 10: Naturalistic analysis of control room activities * Part III: Control room design * Chapter 11: Development of a railway ergonomics control assessment package (RECAR) * Chapter 12: Control room mock-up trials * Chapter 13: Design of alarm systems * Chapter 14: Decision support in process control plants * Chapter 15: Training controllers, interface design and mental workload * Chapter 16: Power generation: The advanced control desk * Chapter 17: Human-centred design for railway applications * Chapter 18: Integrated platform management system design for future naval warships

Task analysis identifies the specific tasks needed to accomplish human actions, and the information, control and task support required to complete those tasks. In the control room design, the functions allocated to personnel shall be performed analysis, and it is identified that the specific task can be accomplished by the personnel. Task analysis can provide one of the bases for the human system interface design decisions; match human performance requirements with human capabilities; provide input to procedure development and provide input to staffing, training, and communications requirements of the plant. The method about task analysis and the screening methodology used to select the tasks for analysis are very important. Usually, the scope of task analysis is divided into two complementary activities: function-based task analysis and traditional task analysis, or operational sequence analysis. Function-based task analysis is the functional decomposition (goal-means analysis) for normal power operations. The traditional task analysis, or operational sequence analysis is developed for a representative set of operational and maintenance tasks. The operational sequence analysis include OSA-1 and OSA-2.The task analysis considers alerts, such as alarms and warnings, decision-making, response, teamwork and communication, workload task support, workplace factors, situational and performance shaping factors and hazard identification. The paper also describes the selected basis of selecting the operational sequence to be analyzed in the operational sequence analysis. The method about task analysis and the screening methodology used to select the tasks for analysis are very important. The objective of task analysis review is to verify that the applicant undertook analyses identifying the specific tasks needed to accomplish personnel functions, and also the alarms, information, control- and task-support required to complete those duties. The paper mainly describes not only the above content, but also the reviewing work about task analysis and questions found in reviewing. In this article, there are some examples about the function-based task analysis. At last, the verification for task analysis is addressed simply.

This paper presents an implementation of automation scheme for control of three phase Permanent Magnet Synchronous Motor (PMSM) drive. Performance evaluation and monitoring of drive is described using Supervisory Control and Data Acquisition (SCADA) and Programmable Logic Controller (PLC) system. The control, operation and monitoring of PMSM drive in three basic modes, i.e. position, speed and torque modes is achieved through PLC programming and SCADA. A Human Machine Interface (HMI) control is also developed for operation of drive system at field level controls. Ladder logic programs according to desired control mode of operations are developed to control and monitor the status of PMSM drive. SCADA screens have been developed to control and monitor the status of the motor and for field level control HMI touch screens are designed. The real time data related to PMSM drive such as output of position encoder, torque developed by motor, power input to motor, speed etc. are accessed for supervisory control of drive.

In the modern industrial control landscape, Supervisory Control and Data Acquisition (SCADA) systems serve as critical intermediaries in automating and managing complex processes across many industries, including energy, manufacturing, and utilities. While maintaining the availability and efficiency of these systems is essential, their increased integration into networked environments has exposed them to a growing array of cyber threats. As SCADA systems continue to grow and be deployed globally, malicious actors are increasingly target critical infrastructure, making security management progressively more challenging. Our research explores the benefits of conducting forensic investigations focused on SCADA Human-Machine Interface (HMI) systems, emphasizing how centralized equipment analysis can help overcome the unique challenges these systems present. To assist investigators in efficiently collecting system-wide data from SCADA HMI environments, we developed a forensic analysis framework that enables the evaluation of system discrepancies and evidence of potential cyberattacks. Additionally, we present a comprehensive forensic analysis of a SCADA testbed featuring Ignition, a popular SCADA software platform developed by Inductive Automation. Our investigation reveals that SCADA HMI forensics can provide valuable insight into the system's state, allowing for the identification and cross-analysis of critical equipment and operational data across memory, network, and disk. This framework is further supported by the creation of the Ignition Forensic Artifact Carving Tool (IFACT), a SCADA HMI Forensic Analysis Tool designed to assist in extracting artifacts and parsing system information from forensic data sourced from Ignition HMIs. Using IFACT, we achieve accurate insights into device and equipment data in SCADA systems, investigating data persistence in volatile memory and the variability of its lifetime based on the system state.

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 230051, “An Integrated Approach for Scheduling and Validation of Steady-State Production-Well Tests in Unconventional Wells,” by Emmanouil Karantinos, XTO Energy, and Akshith Yalala and Craig Ellis Newlin, ExxonMobil, et al. The paper has not been peer-reviewed. _ Steady-state production-well tests are a key component of day-to-day operations, providing critical data for regulatory reporting, volume allocation, and identification of well-work opportunities. This paper presents an automated workflow deployed for scheduling and validating steady-state production-well tests across more than 2,300 of the operator’s wells in the Permian Basin. Field Instrumentation and Well-Testing Procedure Permian Basin wells typically produce fluids containing vapor and liquid hydrocarbon phases and water. Produced fluids are routed by a well header, either a three-phase production (bulk) separator or a three-phase test separator where a single well is tested. A standard three-phase separator is configured such that the produced fluid is separated into gas, water, and liquid hydrocarbons using gravity separation. A steady-state production-well test is initiated by physically routing a well into a test separator through the manual well-header valve or through an automated actuating valve. Permian Basin operations have elected to install human/machine interfaces (HMI) at the separators to streamline the capture of well-test information, enabling the operator to enter the well on test directly using the HMI with predetermined test durations, typically 8, 12, or 24 hours. At the end of the test, field-automation equipment captures the accumulated volumes over the test period. For each well test, oil, water, and gas volumes are reported by the field-automation equipment and published to cloud databases. Upon the completion of a well test, the produced oil, water, gas, and gas-injection volumes are made available to a mobile application so that field operators can review and approve or reject a production-well test by comparing the current well performance with previous well tests while considering any facility or well events that occurred during the well test. Field-Data Collection The automated well-test validation (WTV) process consists of loosely coupled operational-technology (OT) as well as information-technology processes and systems. The data originates on the edge of the network, typically in a controller such as a programmable logic controller (PLC) or remote terminal unit that communicates with field devices, sensors, and electronic-flow-measurement (EFM) equipment. This data is collected into the controller and runs through either standard third-party well-test programs or internal well-test logic developed by field personnel. A typical well-test data-gathering program features a set of registers to store ongoing and completed well tests and notify other systems that a well test has been completed. Edge-computing resources also run at these locations; these resources connect to and monitor the PLC controller over various OT protocols. Processes on these edge devices then capture the current well-test results and send them to middleware using the message-queuing telemetry transport (MQTT) protocol. Subscribing nodes within the supervisory control and data acquisition (SCADA) system then monitor the data feeding into the MQTT brokers, capture any well-test records, and store this information to a centralized database. The local edge-computing devices publish high-resolution, real-time EFM volumes and associated test-vessel data continually during each well test over MQTT. The subscribing SCADA system historizes this data in both on-premises databases and the cloud, where it is housed as time-series data and used in WTV analytics.

The paper proposes the design of the supervisory heuristic fuzzy control system applied to a Sequencing Batch Reactor (SBR) in the Wastewater Treatment Plant (WWTP). Based on real data records and the biological process and aeration system models, a control system for biological processes has been designed. The supervisory control system performs management of the reactor work cycle, determines the phase length, controls the sludge age, calculates the setpoint of dissolved oxygen, and adapts parameters of the lower control layer. The results of simulation tests for the case study wastewater treatment plant are presented.