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The laser powder bed fusion (L-PBF) additive manufacturing process offers many advantages. However, its industrial integration still needs to be improved due to the certification constraints of the produced parts. Thus, this paper proposes a phenomenological causal chain of process failures to ensure the control of the L-PBF process and further certify the quality of the parts produced. Consequences of unsuitable thermal regimes are analysed using a failure mode and effects analysis (FMEA) approach, allowing a more global understanding of all the causal chain-related data. The proposed approach is based on standard acquisition equipment available on industrial machines and proves relevant for identifying process failures. Experimental validation of the proposed monitoring method is implemented on a use case using dedicated software. Finally, it is shown that the method is relevant in this confrontation and compatible with the time scale of the process for future NC integration and real-time monitoring. [ABSTRACT FROM AUTHOR]

Nowadays many processes in the food industry are monitored in an automatic way, with the purpose of minimising the need for workforce and of ensuring the proper control of the quality and safety of the foodstuff. All the sensors share data with a centralised management unit, where often a Manufacturing Execution System collects and evaluates them. As reported in recent research, however, a further step that can be undertaken, exploiting Industry 4.0 enabling technologies, is the implementation of digital twin approaches, with the additional aim to prevent possible issues during production. In line with these considerations, this work aims at showing two different digital twin models intended for improving the control of as many real food systems. Liquid and powder fluids are taken as examples for highlighting the differences in the optimization of the two food processes, as well as for fully exploring the potential of the digital twin approach. Finally, based on the real data taken from two pilot plants, a framework for the selection of the best digital twin tool in the food sector is delineated. [ABSTRACT FROM AUTHOR]

The use of holding and inspection fixtures is common across many sectors of manufacturing. The concept of a fixture for holding a component, for the purposes of assembly or inspection, is straightforward. The fixture design and the associated clamping strategy can have a significant impact on the process. This paper presents a methodology for investigating the effects of clamping sequence for a production inspection fixture, on the dimensional variability of an automotive production-representative sheet metal sub-assembly, along with experimental findings and analysis of measurement data. The study utilises both a coordinate measuring machine and laser tracker to capture a range of features and surface points, and compares four different clamping sequences, including the manufacturer's defined sequence, to evaluate their effect on the dimensional results from a predetermined measurement plan. The results from the study show that there was significant variation in measurements taken from the four different clamping sequences, and these variations can show the same points and/or features being within tolerance for one clamping sequence and out of tolerance for another. This clearly has major implications for product development and subsequent volume manufacture, so needs to be considered and optimised in the measurement planning process. [ABSTRACT FROM AUTHOR]

Process control is crucial in the operations of chemical engineering plants and manufacturing processes across a broad range of industries. This report details the testing and optimization of P, PI, PID controllers for a temperature control system. The first objective is to determine the best controller type for controlling the system temperature. The second objective is to alter tuning parameters manually for PID controllers in the temperature control system to achieve optimality. The performance criteria include the settling time, peak-to-trough ratio, and steady state offset. It is discovered that PID controller is the best due to its fast response,offset elimination, and minimized settling time and oscillations, combining the aspects of Proportional (P), Integral (I), and Derivative (D) control. Additionally, manual tuning attempts were made to fine-tune the PID controller. However, the lack of data points lead to inconclusive results. Future works should conduct additional trials or employ alternative tuning methods.

In this article, we propose an adaptive top-r method to monitor large-scale data streams where the change may affect a set of unknown data streams at some unknown time. Motivated by parallel and distributed computing, we propose to develop global monitoring schemes by parallel running local detection procedures and then use the Benjamin–Hochberg false discovery rate control procedure to estimate the number of changed data streams adaptively. Our approach is illustrated in two concrete examples: one is a homogeneous case when all data streams are independent and identically distributed with the same known pre-change and post-change distributions. The other is when all data are normally distributed, and the mean shifts are unknown and can be positive or negative. Theoretically, we show that when the pre-change and post-change distributions are completely specified, our proposed method can estimate the number of changed data streams for both the pre-change and post-change status. Moreover, we perform simulations and two case studies to show its detection efficiency. [ABSTRACT FROM AUTHOR]

As the core of artificial intelligence and other emerging information technologies, algorithms have been deeply embedded in business and public decision-making. However, the attributes and operational characteristics of algorithmic automated decision-making, such as the coexistence of virtual and real decision-making entities, the iterative update of algorithmic technology, and the hiding and complexity of causal relationships, have made traditional decision-making governance architecture frequently ineffective. There still exist problems in the current algorithmic decision-making governance, which is mainly based on individual empowerment and due process control, including the lack of boundaries for algorithmic decision-making application, insufficient regulation, unclear public disclosure rules, and difficulties in identifying liability. Based on the superiority of tiered and classified algorithmic decision-making governance in terms of flexible regulation, risk identification and differentiated treatment, this paper constructs a tiered and classified model of algorithmic decision-making that takes into account the application scenarios and risk levels of algorithmic decision-making. The model divides algorithmic decision-making into four types of risk, and sets governance measures combining leniency with severity for different types of risk in view of entry thresholds, regulatory details, public disclosure levels, and scope of liability to create a scenario-based refined algorithmic decision-making governance mechanism in response to the complex architecture and diverse application scenarios of algorithmic decision-making. [ABSTRACT FROM AUTHOR]

This article aims to study the implementation of classical proportional‐integrative (PI) controllers and their coupling with the fuzzy inference systems (FISs) in the act of closed‐circuit grinding (CCG) ball mill system. The system was formed for a multiple‐input multiple‐output (MIMO) system, with two inputs, the feed rate (WF) and speed classifier rotor (VR), and two outputs, a sieve fraction 45 μm (P45) and the amount of material by a weight inside the drum (hold up [HU]). The model was simulated based on experimental processes and control strategies. The fuzzy‐PI controllers were developed on the software, and the data from this process were used to build the database and the necessary knowledge to construct the FIS controllers (with fuzzy rules base 3 × 3 and 5 × 5). Their implementation decreases the error criteria integral of time multiplied by the absolute error (ITAE) and integral of the absolute magnitude of the error (IAE) by 35% and 65%, respectively. Although, applying fuzzy‐PI systems with a smaller rule‐based outcome gives the benefits of implementing the fuzzy logic (FL) but with a smaller oscillatory performance and a minor negative effect on HU control. [ABSTRACT FROM AUTHOR]

Deep geothermal closed-loops have recently gained attention because of their advantages over classical geothermal applications (e.g., less dependence on the geology, no risk of induced seismicity) and technological advantages (e.g., in the drilling process, use of alternative to water fluids). This paper deals with the repurposing of an existing well in Mol, Belgium, by numerically evaluating the closed-loop concept. Two numerical tools are used to predict the evolution of the temperature and the produced energy over a period of 20 years considering the vertical coaxial well and the complete geological morphology. Full-scale simulations are initially carried out to estimate the maximum capacity of the well and to highlight the need to control the output of the well by adjusting the inlet conditions. Simulations are then performed either to deliver a constant power or to cover irregular thermal energy demands of two buildings by applying in both cases three process control operations. Through controlling the inlet temperature, the injected flow rate or successively both, the production of excess energy, resulting from the overdesign of the existing wellbore for the specific application, is limited. The simulations showed that continuous adjustments to the injection temperature and/or flow rate are needed to restrict the rapid drop in outlet temperature and consequent thermal depletion of the rocks, caused by the highly transient nature of the diffusive heat transfer from the rocks to the wellbore, as well as to supply a specific heat demand, constant or irregular, over the long term. In fact, the combination of both controls could be the ideal strategy for supplying the demand at the highest COP. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) uses highly powerful computers to mimic human intelligent behavior; it is a major research hotspot in science and technology, with an increasing number of applications to a wider range of fields, including complex process supervision and control. Wastewater treatment is an example of a complex process involving many uncertainties and external factors to achieve a final product with specific requisites (effluents with prescribed quality). Reducing process energy consumption, greenhouse gas emissions, and resources recovery are additional requirements of these facilities' operation. AI could extend the purpose and the expected results of previously adopted tools and present operational approaches by leveraging superior simulation, prediction, control, and adaptation capabilities. This paper reviews current AI research in the wastewater field and discusses present achievements and potentials. So far, almost all applications in the sector involve predictive studies, often at a small scale or with limited data use. Frontline research aimed at the creation of AI-supported digital twins of real systems is being conducted, with few encouraging but still limited applications. This paper aims at identifying and discussing key barriers to wider AI adoption in the field, which include laborious instrumentation maintenance, lack of process expertise in the design of current software, instability of control loops, and insufficient incentives for resource efficiency achievement. [ABSTRACT FROM AUTHOR]

Laser powder bed fusion (PBF-LB) additive manufacturing (AM) enables production of complex metal parts. The PBF-LB process is, however, prone to the formation of voids, that can compromise the mechanical properties of the final product. Advancements to in-situ sensing and data processing enables the detection of void formation mid-process. If sensing data can be processed efficiently and in real-time, there is the possibility to mitigate voids in-situ, without relying on post-process methods, such as hot isostatic pressing (HIP). Mitigating defects in-situ reduces energy and material expense, limits the need for post-processing, and improves process reliability and consistency. This study investigates two in-situ strategies for targeted void mitigation in PBF-LB of Ti-6Al-4V: (1) targeted intralayer re-melt mitigation (TIRM, re-processing void regions before powder recoating) and (2) targeted interlayer parameter adjustment (TIPA, adjusting the laser power when processing in the void region on the subsequent layer after a void). For each mitigation strategy, the size of the mitigation area relative to the size of the void and the laser power used for mitigation were varied. To systematically assess mitigation success, surrogate voids were programmatically induced during part fabrication at known locations by decreasing the laser power when processing within predetermined regions over sequential layers. This work provides insight into the proper mitigation parameters to effectively heal voids and understanding into the limits of in-situ void mitigation. For both mitigation strategies, optimal mitigation parameters resulted in complete elimination of voids or a significant reduction in void volume. These results indicate that voids detected during PBF-LB AM can be reduced in volume or eliminated in-situ. [ABSTRACT FROM AUTHOR]

Taking the construction content of the section S09 of the Shenzhen-Zhongshan Link as an example, a consortium formed by the CCCC First Harbor Engineering Co., Ltd., the CCCC Fourth Harbor Engineering Co., Ltd. and the CCCC Guangzhou Dredging Co., Ltd., which includes a number of constructions such as bridges, tunnels, artificial islands, and immersed tube prefabrication. It has the characteristics of large scale, tight construction period, many new technologies, and high social attention. In order to facilitate the efficient management of large-scale key projects, new models have been explored and practiced in the process of project construction organization, including the establishment of organizational structure, communication mechanism, schedule management, safety and environmental protection management, etc. The consortium model has been tested for 6 years, successfully completed various node tasks and under its operation and command, and successfully carried out a number of innovative researches, which has been highly affirmed by the society and the owners. This management model can be used as a reference for similar large-scale consortium projects. [ABSTRACT FROM AUTHOR]

Food unit operations refer to the engineering processes involved in transforming raw materials into desirable food products, taking into account the main laws and principles that govern the physical, chemical, and biochemical changes related to these processes. Drying is one of the most common unit operations used in the food sector to reduce food water content, thereby extending shelf-life, reducing weight and volume, and decreasing inventory and transportation costs. Traditionally, food materials are dried using conventional methods, such as natural solar drying and hot air drying. However, recent years have witnessed the introduction of several emerging technologies (e.g., infrared drying, microwave drying, and freeze drying) that have promising potential to overcome challenges, such as uneven drying, poor sensory properties and nutrient loss, and large energy consumption. More interestingly, recent developments and advancements in digital, physical, and biological technologies, spurred by the Fourth Industrial Revolution (Industry 4.0), have significantly impacted various food manufacturing operations, including food drying. Growing evidence shows that diverse Industry 4.0 technologies (notably artificial intelligence, the Internet of Things, smart sensors, digital twins, and big data) can be harnessed to improve the modelling, monitoring, prediction, and optimization of various parameters in food drying. These technological advancements are not only accelerating the pace of innovation but also enhancing process efficiency and overall performance in intelligent food drying, ushering in the era of "Food Drying 4.0." [ABSTRACT FROM AUTHOR]

Mining and mineral processing are essential for the functioning of many economic sectors and for meeting human needs. Diagnostics and evaluations of faults are necessary to ensure the successful and responsible management of mining and processing processes for mineral raw materials. Fault-free operation contributes to increased efficiency, productivity, safety, and reliability, reduces the cost of the process under consideration, and reduces environmental impacts. This study aims to identify and analyze possible component failures associated with the jaw crusher used in the process of andesite crushing in an open-pit quarry and compare different approaches to their assessment. The benefit of this is using three different failure analysis methods to assess the criticality of individual jaw crusher components. This approach's novelty lies in the synergy that occurs when assessing the failures' impacts on safety, quality, and the environment. [ABSTRACT FROM AUTHOR]

The success of reinforcement learning (RL) combined with deep neural networks has led to the development of numerous RL algorithms that have demonstrated remarkable performance across various domains. However, despite its potential in process control, relatively limited research has explored RL in this field. This paper aims to bridge the gap between RL and process control, providing potential applications and insights for process control engineers. In this review, we first summarize previous efforts to apply RL to process control. Next, we provide an overview of RL concepts and categorize recent RL algorithms, analyzing the strengths and weaknesses of each category. We implement fourteen RL algorithms and apply them to six relevant benchmark environments, conducting quantitative analyses to identify the most suitable approaches for specific process control problems. Finally, we draw conclusions and outline future research directions to advance RL's application in process control. [ABSTRACT FROM AUTHOR]

This perspective paper discusses the alignment between steady‐state design and control (dynamic) simulation in the context of flexibility analysis for distillation systems. Operational variations, such as fluctuations in feed composition or flowrate, can stem from external factors like raw material quality or temperature variations. These disturbances need to be mitigated to ensure optimal industrial performance. Traditionally, these process uncertainties are usually considered in a sequential manner, where the steady‐state flowsheet is established first, and control performance is analyzed afterwards. However, recent studies have started integrating flexibility index into the design phase to account for process uncertainties. While this integration has improved design strategies, aligning steady‐state and dynamic control simulations for comprehensive flexibility analysis remains underexplored. In this paper, we wish to share new perspectives and insights we have observed by analyzing the existing literature. We highlight some points not immediately apparent in our previous studies, hoping these insights will serve as guidelines for future research in this direction. We believe that validating results between steady‐state and control simulations is a long‐term endeavor that cannot be conclusively addressed soon. However, we hope this paper will be valuable to future researchers, contributing to advancing this field and reaching those who will appreciate and build upon these insights. © 2024 Society of Chemical Industry (SCI). [ABSTRACT FROM AUTHOR]

High-throughput and cost-efficient fabrication of intricate nanopatterns using top-down approaches remains a significant challenge. To overcome this limitation, advancements are required across various domains: patterning techniques, real-time and post-process metrology, data analysis, and, crucially, process control. We review recent progress in continuous, top-down nanomanufacturing, with a particular focus on data-driven process control strategies. We explore existing Machine Learning (ML)-based approaches for implementing key aspects of continuous process control, encompassing high-speed metrology balancing speed and resolution, modeling relationships between process parameters and yield, multimodal data fusion for comprehensive process monitoring, and control law development for real-time process adjustments. To assess the applicability of established control strategies in continuous settings, we compare roll-to-roll (R2R) manufacturing, a paradigmatic continuous multistage process, with the well-established batch-based semiconductor manufacturing. Finally, we outline promising future research directions for achieving high-quality, cost-effective, top-down nanomanufacturing and particularly R2R nanomanufacturing at scale. [ABSTRACT FROM AUTHOR]

Operators in modular process plants face new demands due to features like increasing automation and digitalization combined with an architecture allowing for reconfigurations in short time spans. However, operators must be able to master process control tasks at all times. For research purposes on topics like supporting operators in their performance in process control of modular process plants, this article aims at developing scenarios of such plants. Based on three conceptual levels describing the relation of chemical processes and their modularized realization and a neutralization process as use case, four scenarios were developed. Having the common task to increase the throughput, the scenarios differ in terms of complexity and constraints that need to be considered for process control. [ABSTRACT FROM AUTHOR]

This is a study of the cooperative work of making steel in a contemporary steel plant. The study is, first of all, a study of the coordinative practices of a cooperative ensemble of operators controlling a time-critical transformation process, while spatially dispersed at different work stations across the plant, working under quite different and varying local constraints and requirements, with only rudimentary means of ongoing communication. Their individual and local contributions to the overall effort must be minutely synchronized to meet the strict temporal requirements of the operation as a whole. These challenges notwithstanding, the operators manage to act concertedly to produce quality steel and to do so routinely. The question is, how do they manage to do that? As the workers in the setting generally are not able to coordinate their cooperative effort discursively, it is analytically both feasible and necessary to foreground and identify the knowledge of metallurgy of steel and of the plant that enables them, as they go about their own local activities, to apprehend the problems and intentions of their colleagues as reflected in the changing state of the technical processes. The underlying thesis of the study is that in order to answer the general question of how workers engaged in cooperative work are able to heed the activities of their colleagues, and to do so routinely, we are well advised to 'take the concept of practice seriously'. [ABSTRACT FROM AUTHOR]

Control charts are essential in production processes to maintain quality of the products. Inspite of numerous control charts existing for process location under normal model, there is a need for developing control charts when situations demand production process under other distributions. In this paper, a class of control charts based on various midranges is proposed for monitoring location parameter of an ongoing process when process variables follow exponential distribution. The midranges are defined and their distributions are obtained. The performance of some members of the proposed class are evaluated in terms of their power, average run length (ARL), median run length (MRL) and standard deviation of run length (SDRL). Also, optimality and effectiveness of members of the class are discussed along with their illustration through an example. [ABSTRACT FROM AUTHOR]

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