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This paper aims to use redundant manipulators to solve the challenge of collision avoidance in construction operations such as welding and painting.

In this paper, a null-space-based task-priority adjustment approach is developed to avoid collisions. The method establishes the relative position of the obstacle and the robot arm by defining the “link space,” and then the priority of the collision avoidance task and the end-effector task is adjusted according to the relative position by introducing the null space task conversion factors.

Numerical simulations demonstrate that the proposed method can realize collision-free maneuvers for redundant manipulators and guarantee the tracking precision of the end-effector task. The experimental results show that the method can avoid dynamic obstacles in redundant manipulator welding tasks.

A new formula for task priority adjustment for collision avoidance of redundant manipulators is proposed, and the original task tracking accuracy is guaranteed under the premise of safety.

The purpose of this paper is to examine the effectiveness of UK investment firms’ implementation of the requirements in Commission Delegated Regulation 2017/589 (more commonly known as “Regulatory Technical Standard 6” or “RTS 6”) that govern the conduct of algorithmic trading activities.

A qualitative examination of 19 semi-structured interviews with practitioners working for, or with, UK investment firms engaged in algorithmic trading activities.

The paper finds that practitioners generally have a good understanding of the requirements in RTS 6. Some lack knowledge of algorithms, coding and algorithmic strategies but have used best efforts to implement RTS 6. However, regulatory fatigue, complacency, cost pressures, governance in international groups, overreliance on external knowledge and generous risk parameter calibration threaten to undermine these efforts.

The study’s findings are limited to the participants’ insights. Some areas of the RTS 6 regime attracted little comment from participants.

The paper proposes the introduction of mandatory algorithmic trading qualification requirements for key staff; the lessening of the requirements in RTS 6 for automated executors; and the introduction of a recognised software vendor regime to reduce duplication and improve coordination between market participants that deploy algorithmic trading systems.

To the best of the author’s knowledge, the study represents the first qualitative examination of firms’ implementation of the algorithmic trading regime in the second Markets in Financial Instruments Directive 2014/65/EU.

The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

Shorter lead time with low price and quality product demand is pivotal in the garment industry. Pressure on production lead time stresses the importance of reducing style changeover time in manufacturing factories, and this paper aims to contribute to solving the challenge by showing how the single minute exchange of die (SMED) methodology in practice can be adapted to garment factories in developing countries.

The paper investigates three cases of SMED implementation integrated with responsible, accountable, consulted, informed (RACI) matrices in garment factories in an action research approach. Both quantitative and qualitative methods are applied.

The study shows a reduction of 50% to 64% of changeover time with SMED implementation measured with two key indicators – throughout time and time to reach peak production. Moreover, the implementation depends on the application of the RACI matrix for the distribution of responsibility as well as integration with the basic production flow before and after the application of SMED.

The study can guide better SMED implementation in garment factories with limited investment by stressing the need to adapt to the specifics of the garment industry, secure the division of responsibility and integrate SMED in the production flow before and after the changeover.

Limited research on the application of SMED in the garment industry. This paper contributes to understanding the specific conditions for successful implementation in the garment industry in developing countries and addresses additional activities that help secure a sustainable implementation process.

The UK Mental Health Act (MHA) Reform (2021) on race and ethnicity promotes new governmental strategies to tackle inequalities faced by ethnically racialised communities detained under the MHA. However, there is a scarcity in personality disorder and ethnicity research. This study aims to investigate what is available in the UK in relation to prevalence, aetiology and treatment provisions of personality disorder for ethnically diverse patients, and to understand their interconnectedness with mental health and criminal justice service provisions. Three key areas of investigations were reviewed, (1) UK prevalence of personality disorder amongst ethnically diverse individuals; (2) aetiology of personality disorder and ethnicity; (3) treatment provisions for ethnically diverse individuals diagnosed with personality disorder.

A scoping study review involved a comprehensive scanning of literature published between 2003 and 2022. Screening and data extraction tools were co-produced by an ethnically diverse research team, including people with lived experience of mental health and occupational expertise. Collaborative work was complete throughout the review, ensuring the research remained valid and reliable.

Ten papers were included. Results demonstrated an evident gap in the literature. Of these, nine papers discussed their prevalence, three papers informed on treatment provisions and only one made reference to aetiology. This review further supports the notion that personality disorder is under-represented within ethnic minority populations, particularly of African, Caribbean and British heritage, however, the reasons for this are multi-facetted and complex, hence, requiring further investigation. The evidence collected relating to treatment provisions of personality disorder was limited and of low quality to reach a clear conclusion on effective treatments for ethnically diverse patients.

The shortage of findings on prevalence, aetiology and treatment provisions, emphasises the need to prioritise further research in this area. Results provide valuable insights into this limited body of knowledge from a UK perspective.

This research paper aims to optimize the calibration process for an ABB IRB 120 robot, specifically for robotic orbital milling applications, by introducing and validating the use of the observability index and telescopic ballbar for accuracy enhancement.

The study uses the telescopic ballbar and an observability index for the calibration of an ABB IRB 120 robot, focusing on robotic orbital milling. Comparative simulation analysis selects the O₃ index. Experimental tests, both static and dynamic, evaluate the proposed calibration approach within the robot’s workspace.

The proposed calibration approach significantly reduces circularity errors, particularly in robotic orbital milling, showcasing effectiveness in both static and dynamic modes at various tool center point speeds.

The study focuses on a specific robot model and application (robotic orbital milling), limiting generalizability. Further research could explore diverse robot models and applications.

The findings offer practical benefits by enhancing the accuracy of robotic systems, particularly in precision tasks like orbital milling, providing a valuable calibration method.

While primarily technological, improved robotic precision can have social implications, potentially influencing fields where robotic applications are crucial, such as manufacturing and automation.

This study’s distinctiveness lies in advancing the accuracy and precision of industrial robots during circular motions, specifically tailored for orbital milling applications. The innovative approach synergistically uses the observability index and telescopic ballbar to achieve these objectives.

This study aims to dissect the multifaceted impact of ISO/IEC 17025 accreditation, specifically within civil engineering testing and calibration laboratories. To achieve this, it intends to explore several key objectives: identifying the prominent benefits of accreditation to laboratory performance, understanding the advantages conferred through participation in proficiency testing schemes, assessing the role of accreditation in enhancing laboratory competitiveness, examining the primary challenges encountered during the accreditation process, investigating any discernible adverse effects of accreditation on laboratory performance and evaluating whether the financial cost of accreditation justifies the resultant profitability.

This study employs a qualitative approach through semi-structured interviews with 23 industry professionals—including technical managers, quality managers, external auditors and clients. Thematic analysis, guided by Braun and Clarke’s six-stage paradigm, was utilized to interpret the data, ensuring a comprehensive understanding of the accreditation’s impact.

Findings reveal that accreditation significantly enhances operational processes, fosters quality awareness and facilitates continuous improvement, contributing to greater client satisfaction. In addition, standardized operations and rigorous quality controls further result in enhanced performance metrics, such as staff capability and measurement accuracy. However, the study also uncovers the challenges of accreditation, including high resource costs and bureaucratic hurdles that can inhibit innovation and slow routine operations. Importantly, the research underscores that the impact of accreditation on profitability is not universal, but contingent upon various factors like sector-specific regulations and market demand. The study also highlights sector-specific variations in the role of accreditation as a marketing tool and differing perceptions of its value among clients. It further emphasizes the psychological stress of high-stakes evaluations during audits.

This study represents the first in-depth investigation into the impact of ISO/IEC 17025 accreditation on civil engineering testing and calibration laboratories, directly contributing to the enhancement of their quality and operational standards. Providing actionable insights for laboratories, it underscores the importance of weighing accreditation costs and benefits and the necessity for a tailored approach to the unique market and regulatory landscapes they operate in.

Despite a growing body of research focusing on the dark side of sharing economy development, arguments are fragmented and incomplete. This study aims to address the gap by integrating existing viewpoints based on a provider’s perspective.

This study conducted a bibliometric analysis using text mining and clustering algorithm techniques to measure the scope of scientific output on this topic and identify the main research themes.

Through the bibliometric analysis, this study developed an integrative framework based on the platform providers’ internal management issues and external conflicts with consumers, society, government regulations and traditional business. It also identified significant gaps within each research theme and proposed a future research agenda.

Sharing economy development has not yet been fully understood and regulated, leading to unprecedented challenges to existing business systems. The study addresses knowledge gaps and advances the understanding of the dark side of the sharing economy based on the provider’s internal management and interplay with external forces. It offers a roadmap for future research to advance understanding of the “hidden” dark side of the sharing economy.

In a dual-robot system, the relative position error is a superposition of errors from each mono-robot, resulting in deteriorated coordination accuracy. This study aims to enhance relative accuracy of the dual-robot system through direct compensation of relative errors. To achieve this, a novel calibration-driven transfer learning method is proposed for relative error prediction in dual-robot systems.

A novel local product of exponential (POE) model with minimal parameters is proposed for error modeling. And a two-step method is presented to identify both geometric and nongeometric parameters for the mono-robots. Using the identified parameters, two calibrated models are established and combined as one dual-robot model, generating error data between the nominal and calibrated models’ outputs. Subsequently, the calibration-driven transfer, involving pretraining a neural network with sufficient generated error data and fine-tuning with a small measured data set, is introduced, enabling knowledge transfer and thereby obtaining a high-precision relative error predictor.

Experimental validation is conducted, and the results demonstrate that the proposed method has reduced the maximum and average relative errors by 45.1% and 30.6% compared with the calibrated model, yielding the values of 0.594 mm and 0.255 mm, respectively.

First, the proposed calibration-driven transfer method innovatively adopts the calibrated model as a data generator to address the issue of real data scarcity. It achieves high-accuracy relative error prediction with only a small measured data set, significantly enhancing error compensation efficiency. Second, the proposed local POE model achieves model minimality without the need for complex redundant parameter partitioning operations, ensuring stability and robustness in parameter identification.

The purpose of this paper is to propose a system dynamic simulated process model for maintenance work management incorporating the Fourth Industrial Revolution (4IR) technologies.

The extant literature in physical assets maintenance depicts that poor maintenance management is predominantly because of a lack of a clearly defined maintenance work management process model, resulting in poor management of maintenance work. This paper solves this complex phenomenon using a combination of conceptual process modeling and system dynamics simulation incorporating 4IR technologies. A process for maintenance work management and its control actions on scheduled maintenance tasks versus unscheduled maintenance tasks is modeled, replicating real-world scenarios with a digital lens (4IR technologies) for predictive maintenance strategy.

A process for maintenance work management is thus modeled and simulated as a dynamic system. Post-model validation, this study reveals that the real-world maintenance work management process can be replicated using system dynamics modeling. The impact analysis of 4IR technologies on maintenance work management systems reveals that the implementation of 4IR technologies intensifies asset performance with an overall gain of 27.46%, yielding the best maintenance index. This study further reveals that the benefits of 4IR technologies positively impact equipment defect predictability before failure, thereby yielding a predictive maintenance strategy.

The study focused on maintenance work management system without the consideration of other subsystems such as cost of maintenance, production dynamics, and supply chain management.

The maintenance real-world quantitative data is retrieved from two maintenance departments from company A, for a period of 24 months, representing years 2017 and 2018. The maintenance quantitative data retrieved represent six various types of equipment used at underground Mines. The maintenance management qualitative data (Organizational documents) in maintenance management are retrieved from company A and company B. Company A is a global mining industry, and company B is a global manufacturing industry. The reliability of the data used in the model validation have practical implications on how maintenance work management system behaves with the benefit of 4IR technologies' implementation.

This research study yields an overall benefit in asset management, thereby intensifying asset performance. The expected learnings are intended to benefit future research in the physical asset management field of study and most important to the industry practitioners in physical asset management.

This paper provides for a model in which maintenance work and its dynamics is systematically managed. Uncontrollable corrective maintenance work increases the complexity of the overall maintenance work management. The use of a system dynamic model and simulation incorporating 4IR technologies adds value on the maintenance work management effectiveness.