Subjectivity in Failure Mode Effects Analysis (FMEA) Severity Classification within a Reliability Centered Maintenance (RCM) Context

This research paper investigated subjectivity in the severity rating of failure modes within a risk analysis process. Although several risk analysis processes can be utilized, the study considered the application of Failure Modes Effects Analysis (FMEA) or Failure Modes Effects and Criticality Analysis (FMECA) due to its common use within the Aerospace Industry. The study investigated both differences in severity selection given varying amounts of experience as well as any association between severity selection and the provided input information. The main goal of the research was to investigate the impact of data quality on severity selection and to identify factors that impact the severity score, and thus greatly influence the overall risk reduction strategies both in new acquisition and fielded systems. Participants consisted of both experienced and inexperienced FMEA/FMECA users. Participants were tasked to select a severity rating for nine failure modes (across three trials) assuming a typical severity scale. Different input data sets were provided in each trial to ascertain if an association exits between severity class selection and the amount of information available during analysis. This study provided evidence that risk analysis participants are subjective during severity rating selection when utilizing FMEA/FMECA processes. Users who are provided with irrelevant failure and mishap data tend to select similar severity levels; however, when no information is provided to users, user selections will be dramatically more conservative. Participants appear to select similar severity ratings regardless of the relevancy of the provided data

Electromyography & Portable Computing Devices: What Forearm Muscles Should be Measured?

Portable computing devices have become more lightweight and mobile due to changes in the hardware of the devices. In many cases, hardware keyboards are being replacing virtual keyboards, raising concerns on changing ergonomic exposures as, for example, muscle activation patterns may vary with virtual keyboard use. The objective was to identify active forearm muscles across select computing devices. Twenty participants completed a single test session in which seven forearm muscles were evaluated using surface EMG whilst they typed on two portable computing devices (netbook and slate computer) for 5 minutes apiece. Mean normalized EMG was analyzed and indicated that slate computers resulted in significantly lower muscle activation levels than netbooks. The extensor carpi radialis, extensor carpi ulnaris, extensor digitorum communis had the highest muscle activation levels for both the slate and netbook computers. This indicates that the same muscles should be studied for both slate and netbook computers

Application of Advanced Early Warning Systems with Adaptive Protection

This project developed and field-tested two methods of Adaptive Protection systems utilizing synchrophasor data. One method detects conditions of system stress that can lead to unintended relay operation, and initiates a supervisory signal to modify relay response in real time to avoid false trips. The second method detects the possibility of false trips of impedance relays as stable system swings “encroach” on the relays’ impedance zones, and produces an early warning so that relay engineers can re-evaluate relay settings. In addition, real-time synchrophasor data produced by this project was used to develop advanced visualization techniques for display of synchrophasor data to utility operators and engineers

Interaction Effects Of Wrist And Forearm Posture On The Prediction Of Carpal Tunnel Syndrome Cases Within A Fish-Processing Facility

Deviated wrist posture has been implicated as a risk factor for carpal tunnel syndrome (CTS), although alone it has not been found to have a causal relationship with CTS. Studies investigating deviated wrist posture have quantified posture in a single plane of motion and not interactions of wrist postures in multiple planes. The objective of this cross-sectional study was to investigate the ability of wrist and forearm posture interaction effects to predict CTS among a population of fish processing operators. A total of 53 participants performing five job tasks were evaluated using electrogoniometers. Due to task asymmetry, each hand was evaluated separately and treated independently, providing 106 hands as data observations. Using logistic regression analysis it was found that a model including flexed (F), extended (E), the interaction of length of employment (LE) by FE, and the interaction of LE by FE by pronation/supination (PS) accurately classified 78% of all hands as cases or non-cases. The sensitivity of the final model was approximately 48%. The developed model was found to have superior predictive ability when compared to models not considering interaction terms, indicating that posture interactions may in fact have a significant effect on CTS alone

The Use Of Continuous Exposure Data For Predicting Cts In Fish Processing Operators

Carpal tunnel syndrome (CTS) remains one of the most commonly reported and studied work related musculoskeletal disorders. Categorical representations of exposures has been critical in identifying associations between risk factors and CTS, however, quantification of exposure-response relationships require using continuous exposure data. Also, few interactions between risk factors, especially between risk factor categories, have been investigated. The objectives of this study were to investigate the utility of using continuous exposure data and to identify interaction effects of risk factors, both within and between risk factor categories, for predicting CTS. A cross sectional study was performed at a fish processing facility in which 53 participants were evaluated during normal task performance. Due to task asymmetry, each hand was considered separately, providing 106 hands for analysis. Direct measurement and a questionnaire were used to quantify exposures to common occupational and personal risk factors. Stepwise logistic regression analysis was performed to identify three models for predicting CTS and assess predictive ability using: occupational risk factors only (three-way interactions considered), personal risk factors only (two-way interactions considered), and a mixed model considering two-way interactions across risk factor categories and previously identified significant interactions. Models including only occupational or personal risk factors were moderately accurate overall (73% and 77% respectively), but were not sensitive in differentiating between CTS cases and non-cases (39% and 33% respectively). The mixed model was found to be accurate (88%) and sensitive (78%), though only one interaction effect was included. The results of this study illustrate the importance of using continuous exposure data, especially in job tasks where exposures to occupational risk factors is similar, when differentiating between high and low risk job tasks

Driver sitting comfort and discomfort (part I): Use of subjective ratings in discriminating car seats and correspondence among ratings

Several subjective rating schemes were investigated to determine which might be the most effective for use in designing and evaluating car seats, and what relationships exist among these schemes. Participants (n=27) completed short-term driving sessions, in six combinations of seats (from vehicles ranked high and low on overall comfort), vehicle class (sedan and SUV), and driving venue (lab-based and field). Overall ratings were obtained, as well as separate measures of comfort and discomfort of the whole body and local body parts. No association was found between subjective ratings and a publicly available overall vehicle comfort score (J.D. Power and Associates' Comfort Score), implying that other factors besides sitting comfort/discomfort (and car seats) account for overall vehicle comfort. Other major results were that contemporary car seats appear to best accommodate those of middle stature, that packages/seats of sedans were preferred over those of SUVs, that separate processes appeared to be involved in determining whole body comfort and discomfort, and that ratings of comfort were most effective at differentiating among the car seats. Finally, a scheme for the use of subjective ratings was suggested: discomfort ratings for ensuring basic seat requirements (pain prevention-oriented) and comfort ratings for promoting advanced seat requirements (pleasure promotion-oriented). Relevance to industry: Evidence regarding the advantages and disadvantages of different subjective rating schemes can facilitate future design and evaluation of automotive seats.close2

A Model To Predict Accommodations Needed By Disabled Persons

In this paper, several approaches to assist employers in the accommodation process for disabled employees are discussed and a mathematical model is proposed to assist employers in predicting the accommodation level needed by an individual with a mobility-related disability. This study investigates the validity and reliability of this model in assessing the accommodation level needed by individuals utilizing data collected from twelve individuals with mobility-related disabilities. Based on the results of the statistical analyses, this proposed model produces a feasible preliminary measure for assessing the accommodation level needed for persons with mobility-related disabilities. Suggestions for practical application of this model in an industrial setting are addressed. © 2005 IEEE

Enhancing digital driver models: Identification of distinct postural strategies used by drivers

Driver workspace design and evaluation is, in part, based on assumed driving postures of users and determines several ergonomic aspects of a vehicle, such as reach, visibility and postural comfort. Accurately predicting and specifying standard driving postures, hence, are necessary to improve the ergonomic quality of the driver workspace. In this study, a statistical clustering approach was employed to reduce driving posture simulation/prediction errors, assuming that drivers use several distinct postural strategies when interacting with automobiles. 2-D driving postures, described by 16 joint angles, were obtained from 38 participants with diverse demographics (age, gender) and anthropometrics (stature, body mass) and in two vehicle classes (sedans and SUVs). Based on the proximity of joint angle sets, cluster analysis yielded three predominant postural strategies in each vehicle class (i. e. ` lower limb flexed', ` upper limb flexed' and ` extended'). Mean angular differences between clusters ranged from 3.8 to 52.48 for the majority of joints, supporting the practical relevance of the distinct clusters. The existence of such postural strategies should be considered when utilising digital human models (DHMs) to enhance and evaluate driver workspace design ergonomically and proactively.close4