PHYSICAL TASKS:ERGONOMICS PROGRAMS IN INDUSTRY

By -

ERGONOMICS PROGRAMS IN INDUSTRY

An important component of musculoskeletal disorders management efforts is development of a well- structured and comprehensive ergonomic program. According to Alexander and Orr (1992), the basic components of such a program should include:

1. Health and risk-factor surveillance

2. Job analysis and improvement

3. Medical management

4. Training

5. Program evaluation

An excellent program must include participation of all levels of management, medical, safety and health personnel, labor unions, engineering, facility planners, and workers and contain the following elements:

1. Routine (monthly or quarterly) reviews of the OSHA log for patterns of injury and illness and using of special computer programs to identify problem areas.

2. Workplace audits for ergonomic problems are a routine part of the organization’s culture (more than one audit annually for each operating area). Problems identified in this manner are dealt with quickly.

3. List maintained of most critical problems—jobs with job title clearly identified. Knowledge of these problem jobs is widespread, including knowledge by management and the workers.

4. Use of both engineering solutions and administrative controls and seeking to use engineering solutions for long-term solutions.

5. Design engineering is aware of ergonomic considerations and actively builds them into new or reengineered designs. People are an important design consideration.

6. Frequent refresher training for the site-appointed ergonomists in ergonomics and access to short courses and seminars.

Comments

Post a Comment

Popular posts from this blog

DUALITY THEORY:THE ESSENCE OF DUALITY THEORY

By -
Image
THE ESSENCE OF DUALITY THEORY Given our standard form for the primal problem at the left (perhaps after conversion from another form), its dual problem has the form shown to the right. Thus, with the primal problem in maximizatio n form, the dual problem is in minimization form instead. Furthermore, the dual problem uses exactly the same pa r amete r s as the primal problem, but in different locations, as summarized below. 1. The coefficients in the objective function of the primal problem are the right-hand sides of the functional constraints in the dual problem. 2. The right-hand sides of the functional constraints in the primal problem are the coef- ficients in the objective function of the dual problem. 3. The coefficients of a variable in the functional constraints of the primal problem are the coefficients in a functional constraint of the dual problem. To highlight the comparison, now look at these same two problems in matrix notation (as introduced at the beginn...
Read more

NETWORK OPTIMIZATION MODELS:THE MINIMUM SPANNING TREE PROBLEM

By -
Image
THE MINIMUM SPANNING TREE PROBLEM The minimum spanning tree problem bears some similarities to the main version of the shortest-path problem presented in the preceding section. In both cases, an undi r ecte d and connected network is being considered, where the given information includes some mea- sure of the positive length (distance, cost, time, etc.) associated with each link. Both problems also involve choosing a set of links that have the shortest total length among all sets of links that satisfy a certain property. For the shortest-path problem, this property is that the chosen links must provide a path between the origin and the destination. For the minimum spanning tree problem, the required property is that the chosen links must provide a path between ea c h pair of nodes. The minimum spanning tree problem can be summarized as follows: 1. You are given the nodes of a network but not the links. Instead, you are given the po- tential links and the positive length for each ...
Read more

INTEGER PROGRAMMING:THE BRANCH-AND-CUT APPROACH TO SOLVING BIP PROBLEMS

By -
TH E BRANCH-AND-CUT APPROACH TO SOLVING BIP PROBLEMS Integer programming has been an especially exciting area of OR since the mid-1980s be- cause of the dramatic progress being made in its solution methodology. Background To place this progress into perspective, consider the historical background. One big break- through had come in the 1960s and early 1970s with the development and refinement of the branch-and-bound approach. But then the state of the art seemed to hit a plateau. Rel- atively small problems (well under 100 variables) could be solved very efficiently, but even a modest increase in problem size might cause an explosion in computation time be- yond feasible limits. Little progress was being made in overcoming this exponential growth in computation time as the problem size was increased. Many important problems arising in practice could not be solved. Then came the next breakthrough in the mid-1980s, with the introduction of the b r an c h- and-cu t approach to sol...
Read more