Task Analysis For Error Identification Research Articles

Design of Ergonomic Assault Vest for Indonesian Army with Modular Concept

Assault vest is one of crucial products for Indonesian army infantry soldiers to support their activities in the battlefield. Despite its importance, however, the design of the assault vest of Indonesian army was not considered Ergonomics aspects. Based on the deep interview and questionnaries distributed to 30 Indonesian Army infantry soldiers, the current design was not really comfortable and limit the freedom of movement in the battlefield. Because of this, this research aims to design a modular assault vest for Indonesian army infantry that considering Ergonomics aspects. The object of this study was the 411 Infantry Batalyon / Pandawa located in Salatiga City, Central Java Province, with a total sample of 30 active infantry soldiers involve in this study. The research was conducted by using Nordic Body Map method, questionnaire, deep interview, and TAFEI (Task Analysis for Error Identification) as well as Kansei Engineering. The prototype was built to test the proposed assault vest design. A physiological test using the physiological test method of Dr. Woldemar Gerschler was conducted to test the prototype and then the results of the data (VO2) are tested by applying t-test statistical analysis to see whether the proposed assault vest design will have better performance than existing assault vest. Physiological tests were carried out by 23 respondents who were members of a football club. The test indicate that the proposed design show better result in terms of oxygen consumption.

Análisis cognitivos de carga mental e identificación del error humano para mejorar la experiencia de usuario

Las personas, en ocasiones, pueden sentirse abrumadas al tratar de interactuar con la tecnología moderna. Ciertos productos de uso cotidiano cuentan con diseños deficientes, por lo que pueden provocar una experiencia insatisfactoria y frustración, produciéndose con ellas una carga mental en el usuario que pueda inducir al error. El uso de técnicas para la identificación del error humano y de la evaluación de carga mental en el diseño y evaluación de productos, puede proporcionar información relevante y útil, para mejorar la experiencia del usuario. El objetivo de este trabajo fue proponer una metodología para integrar la evaluación de carga mental y el análisis del error humano en el diseño de productos. Se evaluó la carga mental mediante la técnica perfil de carga de trabajo, Workload Profile (WP), y se utilizó una metodología de identificación del error humano, Task Analysis For Error Identification (TAFEI), en la configuración de audífonos inalámbricos. Diez usuarios participaron voluntariamente en el estudio; sus experiencias en el uso de los audífonos fueron videograbadas. Se utilizaron formularios para evaluar carga mental, y se identificaron errores humanos durante la etapa de configuración de los audífonos con el teléfono móvil. El método utilizado en este trabajo ofrece una mayor sensibilidad en la evaluación de la carga mental y permite determinar los recursos de atención que más se utilizan en la realización de la tarea. Se detectaron dos oportunidades de rediseño, una relacionada con la señal lumínica, y la otra para la identificación de las puntas para cada oído. A partir de los resultados de la aplicación de la metodología propuesta en este estudio, los diseñadores pueden mejorar la interacción entre las personas y los productos.

Human errors identification in operation of meat grinder using TAFEI technique

Received: May 2013, Accepted: December 2013 Background: Human error is the most important cause of occupational and non-occupational accidents. Because, it seems necessary to identify, predict and analyze human errors, and also offer appropriate control strategies to reduce errors which cause adverse consequences, the present study was carried out with the aim of identifying human errors while operating meat grinder and offer suggestions in order to reduce human errors in this human-machine system. Materials and Methods: This is a descriptive study. In this ergonomic study the “Task Analysis for Error Identification (TAFEI)” technique was used in order to identify human errors while operating a meat grinder machine. According to this technique, firstly, tasks of human side of the interaction were described by Hierarchical Task Analysis (HTA) and then the State-Space Diagrams (SSDs) were drawn. Finally, after forming the TAFEI diagrams, the transition matrix table was prepared in order to identify human errors. Results: After completing all the steps of TAFEI technique, the transition matrix table was formed. Results showed 49 illegal transition states; therefore, 49 human errors were identified and described while operating the meat grinder machine. Conclusion: The results of this study showed how and under which conditions may meat grinder users do error in the human-machine interaction. In this regard, possible human errors resulting from non-ergonomic design of Iranian meat grinder machine were identified.

Validating task analysis for error identification: reliability and validity of a human error prediction technique

This paper reports on the theoretical and empirical developments for an error prediction methodology called task analysis for error identification (TAFEI). Other researchers have noted the need for theoretically driven approaches that are able to provide practical utility in error prediction. Theoretical developments include the concept of ‘rewritable routines’, which describe the loop between cognitive processing, action and devices states. This has been proposed as a way of unifying ideas from systems theory and cognitive psychology. The empirical research shows that TAFEI is superior to heuristic methods, which supports the idea that structured methods assist in error prediction. The validation study shows that TAFEI reaches acceptable levels in terms of test – retest reliability and concurrent validity. It is believed that the method has reached a level of maturity after 10 years of development work. This is demonstrated by the many uses to which the method has been put, including that of a design tool.

안전한 제품을 설계하기 위한 새로운 제품위험분석 방법

Today we are observing a lot of injuries. casualties. and property losses that are mainly caused by the defects of products. In order to derive safety designs. which minimize the possibility of such product liability-related accidents. we need to take intoaccount the user-product interaction as an important part of the danger factor analysis. Existing risk analysis techniques. however. have some limitations in detecting comprehensive danger factors that are peculiarly involved in human errors and the functional defects of products. Researches on danger factor analysis regarding the user-product interaction have been carried out actively in ergonomics.br/ In this paper. we suggest a novel product risk analysis technique. which is more objective and systematic compared to the previous ones. by combining a modified TAFEl (Task Analysis For Error Identification) technique with SASA (Systematic Approach to Accident Scenario Analysis) technique. By applying this technique to the product design practice in industry. corporations will be able to improve the product safety. consequently strengthening the competitiveness.br/

Task analysis for error identification: Theory, method and validation

This paper presents the underlying theory of Task Analysis for Error Identification. The aim is to illustrate the development of a method that has been proposed for the evaluation of prototypical designs from the perspective of predicting human error. The paper presents the method applied to representative examples. The methodology is considered in terms of the various validation studies that have been conducted, and is discussed in the light of a specific case study.

Error by design: methods for predicting device usability

This paper introduces the idea of predicting ‘designer error’ by evaluating devices using Human Error Identification (HEI) techniques. This is demonstrated using Systematic Human Error Reduction and Prediction Approach (SHERPA) and Task Analysis For Error Identification (TAFEI) to evaluate a vending machine. Appraisal criteria which rely upon user opinion, face validity and utilisation are questioned. Instead a quantitative approach, based upon signal detection theory, is recommended. The performance of people using SHERPA and TAFEI are compared with heuristic judgement and each other. The results of these studies show that both SHERPA and TAFEI are better at predicting errors than the heuristic technique. The performance of SHERPA and TAFEI are comparable, giving some confidence in the use of these approaches. It is suggested that using HEI techniques as part of the design and evaluation process could help to make devices easier to use.

A Case Study of On-Screen Prototypes and Usability Evaluation of Electronic Timers and Food Menu Systems

Ubiquitous computing in domestic products, although allowing smarter products, can increase the complexity of interfaces that the end user has to face. This case study is an evaluation of an on-screen prototype of a cooker timer and food menu system. The techniques used to evaluate the prototype included questionnaire, user trial, System Usability Scale questionnaire (Brooke, 1996), observation, interview, repertory grid, Hierarchical Task Analysis (Kirwan & Ainsworth, 1992), and Task Analysis for Error Identification (Baber & Stanton, 1991, 1996; Stanton & Baber, 1998). From the usability evaluation a simplified interface was designed that will be taken forward and reevaluated in the future. Issues raised in the case study were first that of increased complexity allowed by increased levels of processing power, and second that of on-screen prototypes and the difference between interacting with traditional desktop computing applications as opposed to a physical product. We highlight in the conclusion that there is a need for those involved in development of on-screen and physical prototypes to work with those involved in human factors and usability to ensure a usable end product.

Human error identification techniques applied to public technology: predictions compared with observed use

In this paper, we consider the use of human error identification (HEI) techniques as a possible alternative to observation studies for product evaluation. The HEI techniques used were Task Analysis for Error Identification (TAFEI) and Predictive Human Error Analysis (PHEA). The comparison was undertaken in connection with the prediction of errors in the use of a ticket vending machine. Two main findings emerged from the study. First, predictions derived from the HEI techniques compared favourably with errors observed in actual machine use. Second, the HEI techniques took far less time than direct observation to reach comparable levels of performance. Such rates suggest that these techniques can be usefully applied to the study of consumer products.

Task analysis for error identification: a methodology for designing error-tolerant consumer products

Abstract This paper presents an approach to the assessment of ‘intelligent’ consumer products. We assume that a primary reason for the difficulties people encounter in their use of intelligent consumer products is the lack of clear, consistent, and logical task sequences. The approach we have developed aims to illustrate the task sequences required for the purposeful use of ‘intelligent’ products, in order to indicate points at which errors, problems or confusions may occur. The approach combines two well proven methodologies (hierarchical task analysis and state space diagrams) to provide a description of human product interaction.

Task analysis for error identification: towards a methodology for identifying human error : Baber, C and Stanton, N In: Contemporary Ergonomics 1991, E J Lovesey (Ed). Taylor & Francis, London, 1991, pp 67–71, 8 refs

Task analysis for error identification: towards a methodology for identifying human error : Baber, C and Stanton, N In: Contemporary Ergonomics 1991, E J Lovesey (Ed). Taylor & Francis, London, 1991, pp 67–71, 8 refs