A Multi-Criteria Decision Model for Prescribing Optimal Ergonomic Action Strategies for Industry

Abstract

Multi-criteria decision analysis is presented as a method for prescribing optimal ergonomic actions for industry in response to Occupational Safety and Health Administration (OSHA) proposed ergonomic requirements. Achieving compliance with OSHA requirements can be costly for an employer, so it is important to properly analyze costs and other factors to achieve an optimal decision. A practical and efficient model is needed for decision makers in industry. For decisions related to occupational safety and health, existing models focus on economic decision factors and offer good methods of correctly analyzing costs and benefits to reach an appropriate economic decision. Unfortunately, existing models give little insight for practical inclusion of intangible decision factors. To fill this void, a strong emphasis of this writing is to provide a model that allows practical and efficient consideration of both economic (net present value of cost, quality, etc.) and intangible (production flexibility, employee morale, etc.) decision factors.This paper begins by describing OSHA’s proposed requirements along with the expected costs for industry compliance and expected penalties for non-compliance. Next, multi-criteria decision models and methods are briefly explained in sufficient detail to allow understanding how decision analysis can be applied to ergonomics. Then, a general prescriptive model is developed as a tool that allows industry decision makers to input their own importance weightings and thereby determine the ergonomic action strategy that is optimal for their unique company. Last, an example of using the model is given based on findings from a literature search. The literature search focused on identifying industry goals, decision criteria, importance weightings, and action strategies. Using a tabular method for weighted evaluation of alternatives, the example concludes with a multi-criteria decision table that prescribes selective automation as an optimal strategy based on the identified action alternatives evaluated with respect to cost, quality, and intangibles.KeywordsDecision MakerAction AlternativeImportance WeightingWeighted EvaluationProduction FlexibilityThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.