Methods engineering

About: Methods engineering is a research topic. Over the lifetime, 262 publications have been published within this topic receiving 2324 citations.

Industrial Engineering Meets Ergonomics Work Analysis

Abstract: ergonomist is still more likely to be asked for redesign than for design recommendations. To some extent, this is a reflection of the lack of widespread integration of ergonomics into the design process. Unfortunately, redesign is typically more expensive and challenging than design, and there are often more constraints. The success of any ergonomics effort will depend partly on performing appropriate analyses, but providing recommendations that will be embraced and implemented is just as important. In practice, this means that recommendations will often need to be approved by people involved in the industrial engineering function perhaps the industrial engineering department or one of its corollaries, such as production planning, quality assurance, and manufacturing engineering. It is therefore important for the industrial ergonomist to work synergistically with others in the organization who are at levels above the ergonomics function. Following a brief discussion of history and some of the conflicts that have developed between ergonomics and industrial engineering, I explore ways that industrial ergonomists can achieve synergy in this kind of environment.

DEA common set of weights based on a multi objective Fractional Programming

Abstract: Data envelopment analysis operates as a tool to appraise the relative efficiency of a set of homogenous decision making units. DEA allows each DMU to take its optimal weight in comparison to other DMUs while a similar condition is considered for other units. This feature threats the comparability of different units because different weighting schemes are used for different DMUs. In this paper, a model is presented to determine a common set of weights to calculate DMUs efficiency. This model is developed based on a multi objective fractional linear programming model that considers the original DEA's results as ideal solution and seeks a set of common weights to evaluate DMUs and increases the model's discrimination power. A numerical example is solved and the proposed method's results are compared to some previous methods. This Comparison has shown the proposed method's advantages in ranking DMUs.