2014-07-01 12:00 - Messages

Design method for multi-user workstations utilizing anthropometry and preference data

Past efforts have been made to design single-user workstations to accommodate users' anthropometric and preference distributions. However, there is a lack of methods for designing workstations for group interaction. This paper introduces a method for sizing workstations to allow for a personal work area for each user and a shared space for adjacent users. We first create a virtual population with the same anthropometric and preference distributions as an intended demographic of college-aged students. Members of the virtual population are randomly paired to test if their extended reaches overlap but their normal reaches do not. This process is repeated in a Monte Carlo simulation to estimate the total percentage of groups in the population that will be accommodated for a workstation size. We apply our method to two test cases: in the first, we size polygonal workstations for two populations and, in the second, we dimension circular workstations for different group sizes.

Source: Mahoney, Joseph M., Kurczewski, Nicolas A., et Froede, Erick W. (2014). Applied Ergonomics
http://dx.doi.org/10.1016/j.apergo.2014.07.003

Évaluation de l’implantation du Programme de prévention des troubles musculo-squelettiques liés au travail du Réseau de santé publique en santé au travail

Le Programme de prévention des TMS liés au travail du Réseau de santé publique en santé au travail (RSPSAT) a été mis en place en avril 2008, suite à la publication d'un document de réflexion sur le rôle de la santé publique en prévention des TMS liés au travail et de proposition des orientations de la Table de concertation nationale en santé au travail (TCNSAT) et de l'Institut national de santé publique du Québec (INSPQ) (Stock et coll., 2005). Ce programme vise l'identification de la présence de TMS liés au travail et des facteurs de risque professionnels associés aux TMS et l'intégration des risques TMS aux programmes de santé spécifiques aux entreprises (PSSE), au même titre que les autres risques à la santé au travail. Il vise également la mobilisation des entreprises ayant des facteurs de risque de TMS importants à s'engager dans des activités de prévention. Un programme à quatre blocs a été proposé. Les membres de la TCNSAT ont décidé de lancer le Programme Réseau de prévention des TMS par étape à travers la province. Ils favorisaient d'abord l'implantation des deux premiers blocs du Programme, en tant qu'offre de service minimal aux établissements concernés lors de l'élaboration ou la mise à jour des PSSE.

Source: http://www.inspq.qc.ca/Default.aspx?pageid=263&pub=1832

A structural equation modelling method to describe work environment risk factors and musculoskeletal symptoms among hospital nurses

OBJECTIVES: Epidemiological studies have shown that musculoskeletal symptoms are frequent occupational injury and disability among nurses in developing countries. Preventive measures were not able to reduce musculoskeletal disorders significantly in nursing profession. This study was performed to provide a comprehensive assessment of the association among risk factors in developing musculoskeletal symptoms.
METHOD: A structural equation model was applied to describe and analyse complex causal relationships from sets of occupational variables involved in musculoskeletal symptoms. A questionnaire was applied to nurses at hospitals affiliated to Semnan Medical Sciences University to collect data on personal and occupational factors and musculoskeletal symptoms. An ergonomic rapid entire body assessment measured work posture risks.
RESULTS: Physical work demand and mental pressure increased the risk of musculoskeletal disorders significantly. Musculoskeletal symptoms increased in nurses who worked for extended hours and experienced frequent unstable work posture. Structural equation model showed that musculoskeletal symptoms were associated directly and indirectly by physical and mental job variables, employment status, age and lifestyle.
CONCLUSIONS: Covarience structural analysis is useful to describe and understand both the direct and indirect effects of variables with complex relationship between risk factors on the prediction of musculoskeletal symptoms.

Source: Dehdashti A. Occup. Environ. Med. 2014; 71(Suppl 1): A68-A68.
http://dx.doi.org/10.1136/oemed-2014-102362.212

Manual handling assessment charts (the MAC tool)

This leaflet includes the Manual Handling Assessment Charts (MAC). MAC is a tool developed to help users identify high-risk workplace manual handling activities.
Employers and safety representatives can use the tool to assess the risks posed by lifting, carrying and team manual handling activities. It will help them understand, interpret and categorise the level of risk of the various known risk factors associated with manual handling activities. MAC has a numerical and colour coding score system to highlight high-risk manual handling tasks.

Source: http://www.hse.gov.uk/pubns/indg383.htm?eban=govdel-publications&cr=02-Jul-2014

Factors in the design of order picking systems that influence manual handling practices

Order picking can be defined as the retrieval of stock keeping units from a warehouse according to a pick list generated from a customer order prior to the despatch of the completed order to the customer.
There is a variety of order picking systems that are used in warehouses and distribution centres and the choice of system will determine the amount and type of manual handling that occurs within those locations. In order to understand the factors that influence the design of order picking systems a literature review was undertaken and telephone interviews were conducted with six industry stakeholders. The stakeholders included were two retailers with distribution networks operating across the UK, two specifiers who design order picking systems of different types and complexity for the end users, and two major suppliers of order picking systems.
The factors that influence the amount of manual handling within warehouses and distribution centres are complex and inter-locking. The key factor is the design of the order picking system, particularly how much automation is used and whether pickers travel between pick slots or whether items are automatically delivered to them. It also depends on the nature of the goods that the warehouse handles. There are financial trade-offs between high capital costs of automated systems, and increased labour costs in manual systems.

Source: http://www.hse.gov.uk/research/rrhtm/rr1004.htm

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