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This study proposes a therblig-based evaluation technique as a new accessibility tool for physical products like home appliances that spinal cord injured users occasionally use. This study recruited nine spinal cord injured users for the interview and observation regarding home appliance usage and analytically structured their usage behaviors using therbligs. The therblig notations eventually referred to actual and potential accessibility issues that spinal cord injured users would encounter when using the home appliances. The primary therblig operations causing accessibility issues for spinal cord injured users were 'reach,' 'move,' 'grasp,' 'position,' and 'use', corresponding to their disability characteristics. In addition, this study proposed a new effective therblig called "hook," which is suitable for better representation of user behavior and accessibility evaluation of spinal cord users. This study provided an interaction-based accessibility evaluation technique, which is easy to learn and apply, especially for physical products. The therblig-based accessibility evaluation method describes the user behavior on a micro-scale and localizes a problematic operation throughout the task process during home appliance usage. Reach, Move, Grasp, Position and Use were the primary problematic therblig operations regarding home appliance usage of spinal cord injured users, resulting in low accessibility. A new therblig 'hook' was developed to describe the user behavior of spinal cord injured users. Therblig evaluation offers a more standardized, easy-to-learn accessibility evaluation method that does not require expertise but provides the latent needs of users. [ABSTRACT FROM AUTHOR]

Industrial robotic arms commonly require specialist knowledge for machine functions. Specifically, training cobots for work sequences is time consuming and complex when task complexity increases, such as through differentiation in tool adaptations or work processes. This research explores robot versatility for a context of domestic environments (such as a kitchen/workshop), where work processes are approached as a hybrid scenario, with setup for integration of a tool variety whereby human-robot teams collaborate. The paper discusses a) novel workflows based on a palette of work tools adopted for robot tooling to translate manual human tasks to human-robot tasks; b) an initial script series for work processes that represents modelling, planning, simulation, and implementation; c) a framework for task division through action sets based on Therbligs that supports users; and d) an empirical evaluation of the approach through a series of user studies. In a post-carbon context, previously autonomous robots are required to become more versatile in terms of productivity, scalability, safety and skill criteria and environmental impact. This research extends beyond traditional kitchens to include workshop and fabrication scenarios characterised by the complexity and variability of task applications, guided by detailed action packages that explore robotic work for modular components or fluid and liquid materials; heat and assembly-based processing; and bridges from food preparation to fabrication and manufacturing tasks.

Industrial robotic arms commonly require specialist knowledge for machine functions. Specifically, training cobots for work sequences is time consuming and complex when task complexity increases, such as through differentiation in tool adaptations or work processes. This research explores robot versatility for a context of domestic environments (such as a kitchen/workshop), where work processes are approached as a hybrid scenario, with setup for integration of a tool variety whereby human-robot teams collaborate. The paper discusses a) novel workflows based on a palette of work tools adopted for robot tooling to translate manual human tasks to human-robot tasks; b) an initial script series for work processes that represents modelling, planning, simulation, and implementation; c) a framework for task division through action sets based on Therbligs that supports users; and d) an empirical evaluation of the approach through a series of user studies. In a post-carbon context, previously autonomous robots are required to become more versatile in terms of productivity, scalability, safety and skill criteria and environmental impact. This research extends beyond traditional kitchens to include workshop and fabrication scenarios characterised by the complexity and variability of task applications, guided by detailed action packages that explore robotic work for modular components or fluid and liquid materials; heat and assembly-based processing; and bridges from food preparation to fabrication and manufacturing tasks. [ABSTRACT FROM AUTHOR]

En Colombia, el sector agrícola presenta dificultades en la integración de tecnologías, específicamente en la recolección manual; este es el caso de los cítricos en Caldas. Este estudio aplicó técnicas de Ingeniería de Métodos en la recolección manual de naranjas, en una finca localizada en Arauca, Caldas, con el fin de comprender la operación de recolección con miras a su estandarización. Los resultados permitieron determinar los elementos que conforman la operación; los movimientos realizados en el surco, las ramas, el árbol y los micromovimientos o therbligs; se identificaron además los movimientos eficientes e ineficientes que pueden ser empleados para el diseño de herramientas, la estandarización del proceso de recolección y la definición de normas de competencia laborales que son aspectos fundamentales para la competitividad del sector citrícola

Numerous studies have been undertaken to examine the efficacy of Predetermined Motion Time Systems, ranging from those questioning the underlying postulates to those contrasting the P.M.T. value with a physiological norm. An opportunity arose to compare a macroscopic M.T.M. value with a time study evaluation of 105 practising work study officers, the medium used for the comparison being six rating films.
The method of computing the basic time is outlined together with the comparative results which, whilst not validating any particular system, are of interest. [ABSTRACT FROM AUTHOR]

The analytical procedure of predetermined motion time systems is based on the premise that time standards can be determined by adding elemental times, fixed once and for all and conceived as universally applicable.
Consequently, it was the aim of the experiments to investigate whether this "additivity of elemental times" can be considered sufficiently accurate in practice.
Experiments proved that influences exist, due to the effect of the motion "Gestalt", which make the presumed additivity of elemental times questionable. However, it is also demonstrated--at least as far as the experiments reported are concerned--that, on the one hand, it appears impossible to allow for such influences in practice since they vary from one person to the next, and that on the other these influences may be considered, in many cases, to be of little significance in relation to other factors.
Finally, some general theoretical considerations concerning the overall accuracy of the predetermined motion time systems are presented. From the curves developed it is suggested that even greater inaccuracies in the elemental times will, in many cases, lead to total times of satisfactory validity. [ABSTRACT FROM AUTHOR]

A probabilistic approach to the development of a simplified work measurement system is presented. As a result of this approach, expected time values and accompanying variances can be calculated for each element under investigation.
General Purpose Date (GPD) and Master Standard Data (MSD), standard data systems which are simplifications of a more detailed predetermined time system, Methods-Time Measurement (MTM), were used to illustrate the applicability of this method.
In order to pursue this probabilistic approach, the various combinations of MTM elements which satisfy each investigated GPD and MSD element have been enumerated. The probability of occurrence of each of these possible combinations has been developed using historical data. Given the time value and the probability of occurrence for each possible combination, the expected time value and accompanying variances were generated for the "simplified" element. [ABSTRACT FROM AUTHOR]

To improve energy efficiency, extensive studies have focused on the cutting parameters optimization in the machining process. Actually, non-cutting activities (NCA) occur frequently during machining and this is a promising way to save energy through optimizing NCA without changing the cutting parameters. However, it is difficult for the existing methods to accurately determine and reduce the energy wastes (EW) in NCA. To fill this gap, a novel Therblig-embedded Value Stream Mapping (TVSM) method is proposed to improve the energy transparency and clearly show and reduce the EW in NCA. The Future-State-Map (FSM) of TVSM can be built by minimizing non-cutting activities and Therbligs. By implementing the FSM, time and energy efficiencies can be improved without decreasing the machining quality, which is consistent with the goal of lean energy machining. The method is validated by a machining case study, the results show that the total energy is reduced by 7.65%, and the time efficiency of the value-added activities is improved by 8.12%, and the energy efficiency of value-added activities and Therbligs are raised by 4.95% and 1.58%, respectively. This approach can be applied to reduce the EW of NCA, to support designers to design high energy efficiency machining processes during process planning. [ABSTRACT FROM AUTHOR]

Changes in the distribution of element or therblig times during practice on assembly tasks have been reported from laboratory studies, but few, if any, have been published from observations made in a factory.
Histograms of element times recorded in a factory training centre on two separate operations are shown, and the change of pattern from a roughly normal distribution to a skewed distribution is clearly recognisable. These results are in line with those from published laboratory results. [ABSTRACT FROM AUTHOR]

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An energy-efficient intelligent manufacturing system could significantly save energy compared to traditional intelligent manufacturing systems that do not consider energy issues. Intelligent energy estimation of machining processes is the foundation of the energy-efficient intelligent manufacturing system. This paper proposes a method for machining activity extraction and energy attributes inheritance to support the intelligent energy estimation of machining processes. Fifteen machining activities and their energy attributes are defined according to their operating and energy consumption characteristics. Activities and energy attributes are extracted mainly from NC program supplemented with blank dimensional information. An effective extraction method of activities and energy attributes is the basis for the intelligent energy calculating of machining process. Based on an investigation on the extraction procedure of activities and energy attributes, energy attributes inheritance method is further discussed. Four types of energy attribute inheritance rules are summarized according to the different inheritance characteristics. Based on these four types of inheritance rules, the energy attributes can be transmitted from activity to Therblig as effective inputs of Therblig-based energy model of machining processes. The proposed methodology is finally demonstrated through two machining cases. [ABSTRACT FROM AUTHOR]

Energy efficiency has become an important factor that should be included in Intelligent Manufacturing due to the increasingly rising energy price and severe energy shortage issues. Energy demand modeling method is the foundation of improving the energy efficiency of manufacturing; therefore, an energy demand modeling methodology for machining processes is proposed. In this method, machining processes are divided into a series of activities, and Therblig, as one of the basic concepts of Motion study, is introduced to represent the basic energy demand unit. Moreover, a mathematical model of energy demand of machining processes is established by linking the activity and Therblig with machining state. Finally, case studies are performed to illustrate the validity and feasibility of the proposed methodology. [ABSTRACT FROM AUTHOR]

Abstract: Machining processes are widely used in manufacturing industries and consume large amounts of energy. Research suggests that it is essential to characterize machining processes energy consumption for low carbon manufacturing. Therblig-based energy demand modeling methodology is a powerful tool to evaluate energy consumption of machining processes quantitatively. Here Therbligs are defined as a set of fundamental motions required for machine tool to perform an operation. However, there is a lack of power models of Therbligs, which makes calculation and optimization of energy consumption hard to carry on. This research aims to develop Therblig power models for calculating the energy supply of computer numerical control (CNC) machine tools using machining process parameters. Power of each Therblig is modeled taking machine tool design and operating parameters into account. The developed parametric power models of each Therblig are tested on two CNC lathes and the results showed that the developed models can provide reliable prediction of Therblig power of CNC machine tools. [Copyright &y& Elsevier]

Robotic Minimally Invasive Surgery, and the engendered computer-integration, offers unique opportunities for quantitative computer-based surgical-performance evaluation. In this work, we examine extension of traditional manipulative skill assessment, having deep roots in performance evaluation in manufacturing industries, for applicability to robotic surgical skill evaluation. This method relies on: defining task-level segmentation of modular sub-tasks/micro-motions called 'Therbligs' that can be combined to perform a given task; and analyzing intra- and inter-user performance variance by studying surgeons' performance over each 'Therbligs'. Any of the performance metrics of macro-motions-from motion-economy, tool motion measurements to handed-symmetry-can now be extended over the micro-motion temporal segments. Evaluation studies were based on video recordings of surgical tasks in two settings: first, we examined performance of two representative manipulation exercises (peg board and pick-and-place) on a da Vinci surgical SKILLS simulator. This affords a relatively-controlled and standardized test-scenarios for surgeons with varied experience-levels. Second, task-sequences from real surgical videos were analyzed with a list of predefined 'Therbligs' in order to investigate its overall usefulness. [ABSTRACT FROM AUTHOR]

Sustainable manufacturing plays a role in ensuring products' economic characteristics and reducing energy and resource consumption by improving the well-being of human workers and communities and maintaining safety. Using robots is one way for manufacturers to increase their sustainable manufacturing practices. Nevertheless, there are limitations to directly replacing humans with robots due to work characteristics and practical conditions. Collaboration between robots and humans should accommodate human capabilities while reducing loads and ineffective human motions to prevent human fatigue and maximize overall performance. Moreover, there is a need to establish early and fast communication between humans and machines in human–robot collaboration to know the status of the human in the activity and make immediate adjustments for maximum performance. This study used a deep learning algorithm to classify muscular signals of human motions with accuracy of 88%. It indicates that the signal could be used as information for the robot to determine the human motion's intention during the initial stage of the entire motion. This approach can increase not only the communication and efficiency of human–robot collaboration but also reduce human fatigue by the early detection of human motion patterns. To enhance human well-being, it is suggested that a human–robot collaboration assembly line adopt similar technologies for a sustainable human–robot collaboration workplace. [ABSTRACT FROM AUTHOR]

The article offers information regarding the study on the changes in therbligs times on a simple task using the four fundamental therbligs including Reach, Grasp, Move and Position, which are involved in all assembly work. It is emphasized that a simple tasked has been chosen for study since the subjects are expected to reach rapidly a high level of performance. Moreover, the use of new apparatus has made possible the accurate and continuous recording of element times throughout several repetitions. Detailed information concerning the apparatus and methods use in the study, as well as the analysis of the results is discussed.

The article presents the theory of therblig. Therblig is the basic unit of time and motion study which requires industrial worker to perform manual operation and referred as an elementary subdivisions of motion cycle. This motion study or productive operation consists of 17 fundamental elements which describe the standardized activity in the industry. These elements are the primary components of the movement pattern and give a positive description on how to improve efficiency and economize time.