Search results

The postponement principle concerns defining when and where value is added, usually referring to hardware components for physical products. However, in modern supply chains, software’s importance is increasing, impacting the timing and location of value-adding operations. Lacking insights into software-driven implications for postponement, we aim at elaborating on the postponement principle by contextualizing its evolution when integrating different objects (i.e. hardware and software).

We adopted an abductive approach to elaborate on the existing knowledge with original empirical insights. A single-case study with four subcases allowed us to explore postponement dimensions in the context of a global high-tech enterprise offering products that integrate hardware and software objects. As global supply chains involve multiple jurisdictions with heterogeneous regulations, we also analyzed in depth the emerging fiscal and legal implications.

Besides where and when value is added, the study illustrates that deciding who (i.e. what legal entity) is carrying out what operation on what kind of object is highly important. Moreover, fiscal and legal implications for the various legal entities strongly depend on what operations are executed and in which jurisdiction (where). The study identifies critical interrelationships among postponement dimensions when integrating hardware and software objects, highlighting the importance of understanding and managing their reciprocity with the emerging fiscal and legal risks.

We elaborate on the postponement principle by contextualizing its applications when integrating hardware and software objects in global supply chains, which include multiple jurisdictions. By formalizing the impact of the who dimension, the study contributes to developing the interorganizational perspective for postponement. Moreover, it extends the traditional cost perspective for postponement beyond the trade-off between responsiveness and cost-efficiency, suggesting that firms applying global postponement should extend their focus to also examine fiscal and legal risks for all the legal entities involved.

The purpose of this paper is to illustrate the growing role of robots in the logistics industry.

Following an introduction, which identifies key challenges facing the industry, this paper discusses robotic applications in warehouses, followed by sections covering transportation and delivery and conclusions.

The logistics industry faces a number of challenges that drive technological and operational changes. Robots are already playing a role within the warehouse sector and more complex applications have recently arisen from developments in artificial intelligence-enabled vision technology. In the transportation sector, autonomous trucks are being developed and trialled by leading manufacturers. Many major logistics companies are involved and limited services are underway. Last-mile delivery applications are growing rapidly, and trials, pilot schemes and commercial services are underway in Europe, the USA and the Far East. The Chinese market is particularly buoyant, and in 2019, a delivery robot was launched that operates on public roads, based on Level-4 autonomous driving technology. The drone delivery sector has been slower to develop, in part due to regulatory constraints, but services are now being operated by drone manufacturers, retailers and logistics providers.

This paper provides details of existing and future applications of robots in the logistics industry.

This chapter is a sociologist’s personal reflection. In it, she recognizes that her mother, a woman from rural Puerto Rico with limited formal education, was actually an informed environmentalist. She taught her children the things she learned growing up as one of the older girls among 11 siblings from a poor family. Her mother’s family members knew a great deal about the environment, for example, how to grow healthy, edible and useful plants in or near the home; and, how – for reasons that seemed implicit to her, not to consume too much sugar in the daily diet. The author and her siblings were taught basic environmental principles through their mother’s shopping and meal preparation in the South Bronx and visits to family members in Puerto Rico. She recalls that her mother knew the importance of fresh produce, something the author only learned through formal education, and that she was an amazing cook. Nothing was wasted and everything tasted better than just good.

The purpose of this study is to plan and develop a cost-effective health-care robot for assisting and observing the patients in an accurate and effective way during pandemic situation like COVID-19. The purposed research work can help in better management of pandemic situations in rural areas as well as developing countries where medical facility is not easily available.

It becomes very difficult for the medical staff to have a continuous check on patient’s condition in terms of symptoms and critical parameters during pandemic situations. For dealing with these situations, a service mobile robot with multiple sensors for measuring patients bodily indicators has been proposed and the prototype for the same has been developed that can monitor and aid the patient using the robotic arm. The fuzzy controller has also been incorporated with the mobile robot through which decisions on patient monitoring can be taken automatically. Mamdani implication method has been utilized for formulating mathematical expression of M number of “if and then condition based rules” with defined input X_j (j = 1, 2, ………. s), and output y_i. The inputs and output variables are formed by the membership functions µ_Aij(x_j) and µ_Ci(y_i) to execute the Fuzzy Inference System controller. Here, Aij and Ci are the developed fuzzy sets.

The fuzzy-based prediction model has been tested with the output of medicines for the initial 27 runs and was validated by the correlation of predicted and actual values. The correlation coefficient has been found to be 0.989 with a mean square error value of 0.000174, signifying a strong relationship between the predicted values and the actual values. The proposed research work can handle multiple tasks like online consulting, continuous patient condition monitoring in general wards and ICUs, telemedicine services, hospital waste disposal and providing service to patients at regular time intervals.

The novelty of the proposed research work lies in the integration of artificial intelligence techniques like fuzzy logic with the multi-sensor-based service robot for easy decision-making and continuous patient monitoring in hospitals in rural areas and to reduce the work stress on medical staff during pandemic situation.

Although the sharing economy improves comfort and convenience, it is yet unclear how it affects subjective well-being. This study aims to offer a conceptual model for understanding the linkages between the antecedents and consequences of subjective well-being in ridehailing services.

Using a non-probabilistic sampling method and a pre-tested survey instrument, 450 responses were collected from January to March 2020. The data were analysed using structural equation modelling.

Experience quality and perceived convenience are correlated with subjective well-being. Perceived value and personal innovativeness were not correlated with subjective well-being, as the former does not contribute to the latter’s development. Continuous usage intention significantly correlated with subjective well-being, followed by customer relationship proneness and advocacy. Regarding gender and age differences, men place higher value on customer relationship proneness than women, while women place higher value on subjective well-being than men. Older users value perceived convenience and customer relationship proneness in ridehailing services more than younger users.

Understanding key factors contributing to user well-being in ridehailing would promote a more affordable mobility sector globally. This understanding would enable ridehailing businesses to create more effective business and marketing plans while prioritising user well-being, thus enhancing user happiness and reducing turnover rates.

This research demonstrates how crucial it is for users’ well-being to have a positive experience and find the service convenient. It also highlights the importance of building strong customer relationships and examines how gender and age influence people’s adoption and use of these services.

Aunque la economía colaborativa mejora la comodidad y conveniencia, aún no está claro cómo afecta al bienestar subjetivo. Ofrecemos un modelo conceptual para comprender las conexiones entre los antecedentes y consecuencias del bienestar subjetivo en los servicios de transporte compartido.

Utilizando un método de muestreo no probabilístico y un instrumento de encuesta previamente probado, se recopilaron 450 respuestas entre enero y marzo de 2020. Los datos fueron analizados utilizando un modelo de ecuaciones estructurales.

La calidad de la experiencia y la percepción de conveniencia están correlacionadas con el bienestar subjetivo. El valor percibido y la innovación personal no se correlacionaron con el bienestar subjetivo, ya que el primero no contribuye al desarrollo del último. La intención de uso continuo se correlacionó significativamente con el bienestar subjetivo, seguida por la propensión a las relaciones con los clientes y la defensa de estos servicios. En cuanto a las diferencias de género y edad, los hombres valoran más la propensión a las relaciones con los clientes que las mujeres, mientras que las mujeres valoran más el bienestar subjetivo que los hombres. Los usuarios mayores valoran más la percepción de conveniencia y la propensión a las relaciones con los clientes en los servicios de transporte compartido que los usuarios más jóvenes.

Esta investigación demuestra lo crucial que es para el bienestar de los usuarios tener una experiencia positiva y encontrar el servicio conveniente. También resalta la importancia de construir relaciones sólidas con los clientes y examina cómo el género y la edad influyen en la adopción y uso de estos servicios.

Comprender los factores clave que contribuyen al bienestar de los usuarios en los servicios de transporte compartido promovería un sector de movilidad más asequible a nivel global. Esta comprensión permitiría a las empresas de transporte compartido crear planes de negocios y marketing más efectivos, priorizando el bienestar de los usuarios y mejorando así su felicidad y reduciendo las tasas de rotación.

尽管共享经济提高了舒适度和便利性, 但它如何影响主观幸福感尚不清楚。我们提供了一个概念模型, 用于理解乘车服务中主观幸福感的前因后果之间的联系。

采用非概率抽样方法和预先测试的调查工具, 在 2020 年 1 月至 3 月期间收集了 450 份回复。数据采用结构方程模型进行分析。

体验质量和感知便利性与主观幸福感相关。感知价值和个人创新性与主观幸福感不相关, 因为前者无助于后者的发展。持续使用意愿与主观幸福感密切相关, 其次是客户关系倾向和拥护。在性别和年龄差异方面, 男性比女性更重视客户关系倾向, 而女性比男性更重视主观幸福感。老年用户比年轻用户更重视乘车服务中的便利感和客户关系代言。

这项研究表明, 用户获得积极的体验和便捷的服务对他们的福祉至关重要。研究还强调了建立牢固的客户关系的重要性, 并探讨了性别和年龄如何影响人们采用和使用这些服务。

了解有助于提高乘车旅行用户幸福感的关键因素, 将在全球范围内推动建立一个更加经济实惠的移动出行行业。这种理解将使打车企业能够制定更有效的业务和营销计划, 同时优先考虑用户福祉, 从而提高用户幸福感并降低流失率。

Collaborative robots (cobots) are widely used in various manipulation tasks within complex industrial environments. However, the manipulation capabilities of cobot manipulation planning are reduced by task, environment and joint physical constraints, especially in terms of force performance. Existing motion planning methods need to be more effective in addressing these issues. To overcome these challenges, the authors propose a novel method named force manipulability-oriented manipulation planning (FMMP) for cobots.

This method integrates force manipulability into a bidirectional sampling algorithm, thus planning a series of paths with high force manipulability while satisfying constraints. In this paper, the authors use the geometric properties of the force manipulability ellipsoid (FME) to determine appropriate manipulation configurations. First, the authors match the principal axes of FME with the task constraints at the robot’s end effector to determine manipulation poses, ensuring enhanced force generation in the desired direction. Next, the authors use the volume of FME as the cost function for the sampling algorithm, increasing force manipulability and avoiding kinematic singularities.

Through experimental comparisons with existing algorithms, the authors validate the effectiveness and superiority of the proposed method. The results demonstrate that the FMMP significantly improves the force performance of cobots under task, environmental and joint physical constraints.

To improve the force performance of manipulation planning, the FMMP introduces the FME into sampling-based path planning and comprehensively considers task, environment and joint physical constraints. The proposed method performs satisfactorily in experiments, including assembly and in situ measurement.

The purpose of this systematic review is to critically analyze pharmaceutical industry case studies on the implementation of Lean 4.0 methodologies to synthesize key lessons, benefits and best practices. The goal is to inform decisions and guide investments in related technologies for enhancing quality, compliance, efficiency and responsiveness across production and supply chain processes.

The article utilized a systematic literature review (SLR) methodology following five phases: formulating research questions, locating relevant articles, selecting and evaluating articles, analyzing and synthesizing findings and reporting results. The SLR aimed to critically analyze pharmaceutical industry case studies on Lean 4.0 implementation to synthesize key lessons, benefits and best practices.

Key findings reveal recurrent efficiency gains, obstacles around legacy system integration and data governance as well as necessary operator training investments alongside technological upgrades. On average, quality assurance reliability improved by over 50%, while inventory waste declined by 57% based on quantified metrics across documented initiatives synthesizing robotics, sensors and analytics.

As a comprehensive literature review, findings depend on available documented implementations within the search period rather than direct case evaluations. Reporting bias may also skew toward more successful accounts.

Synthesized implementation patterns, performance outcomes and concealed pitfalls provide pharmaceutical leaders with an evidence-based reference guide aiding adoption strategy development, resource planning and workforce transitioning crucial for Lean 4.0 assimilation.

This systematic assessment of pharmaceutical Lean 4.0 adoption offers an unprecedented perspective into the real-world issues, dependencies and modifications necessary for successful integration, absent from conceptual projections or isolated case studies alone until now.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

This study aims to observe and discuss an emerging disintermediation in transportation, finance and health care, and explain how these three key areas depend on intermediary institutions that are the fruit of modern corporate governance conditions that find their roots in classical sociological theory.

The authors review and incorporate a diversity of research literature to explain the likelihood for the development and continuation of disintermediation.

The authors map two sociological perspectives (Emile Durkheim’s theory of interdependence and Herbert Spencer’s theory of contracts) to two modern corporate governance theories (resource dependence theory and agency theory). The authors then discuss the challenging social situation resulting from modern corporate governance and show how these conditions create the potential for a continuum of disintermediation across the specific and crucial economic sectors of transportation, finance and health care.

The implications of this theoretical integration can help organizational leaders navigate complex social and strategic issues and prepare for the consequences that may result from the emerging disintermediation.

This study aims to investigate the influence of different solder alloy materials on passive devices during laser soldering process. Solder alloy material has been found to significantly influence the solder joint’s quality, such as void formation that can lead to cracks, filling time that affects productivity and fillet shape that determines the solder joint’s reliability.

Finite volume method (FVM)-based simulation that was validated using real laser soldering experiment is used to evaluate the effect of various solder alloy materials, including SAC305, SAC387, SAC396 and SAC405 in laser soldering. These solders are commonly used to assemble the pin-through hole (PTH) capacitor onto the printed circuit board.

The simulation results show how the void ratio, filling time and flow characteristics of different solder alloy materials affect the quality of the solder joint. The optimal solder alloy is SAC396 due to its low void ratio of 1.95%, fastest filling time (1.3 s) to fill a 98% PTH barrel and excellent flow characteristics. The results give the ideal setting for the parameters that can increase the effectiveness of the laser soldering process, which include reducing filling time from 2.2 s to less than 1.5 s while maintaining a high-quality solder joint with a void ratio of less than 2%. Industries that emphasize reliable soldering and effective joint formation gain the advantage of minimal occurrence of void formation, quick filling time and exceptional flowability offered by this solution.

This research is expected not only to improve solder joint reliability but also to drive advancements in laser soldering technology, supporting the development of efficient and reliable microelectronics assembly processes for future electronic devices. The optimized laser soldering material will enable the production of superior passive devices, meeting the growing demands of the electronics market for smaller, high-performance electronic products.

The comparison of different solder alloy materials for PTH capacitor assembly during the laser soldering process has not been reported to date. Additionally, volume of fluid numerical analysis of the quality and reliability of different solder alloy joints has never been conducted on real PTH capacitor assemblies.