The decline of the US manufacturing industry and the economic, social, and environmental burden associated with it have been blamed on the disconnect between executive-level and operational decision-making. The current practice of increasingly compartmentalizing enterprises into profit centers that are coordinated by purely financial considerations aggravates this development. Apart from policy changes, remedying this situation requires the availability of decision-making technology that permits direct consideration of the sustainability impact at all levels of the enterprise. One prerequisite for such technology is that charges for burdens on sustainability are assessed at the most elemental level and can be aggregated to the level of a product, an enterprise or a nation. A framework for this was presented in a paper previously published by this author. Although strictly speaking not a tax, it was labeled “Burden Added Tax” and functions much like the value added tax in effect in many countries. Based on this framework, the present paper describes a novel model for decision-making that can minimize burdens on sustainability at the operational level. The model is focused on the condition of productive assets. The use of object-based modeling makes it possible to faithfully represent reality; to easily adapt the model to changing conditions; and to scale it to the enterprise level. It also makes it possible to easily translate the model into a computer system for static optimization, simulation, and real-time control. The paper concludes with a discussion of the policy implications of the model, challenges faced by an implementation, and strategies and institutional arrangements to realize successful implementation and to achieve true sustainability of productive operations.
|Keywords:||Sustainable Management, Condition Management, System Optimization, Enterprise Optimization, Resource Economics|
Visting Professor, Department of Civil, Construction, and Environmental Engineering, San Diego State University, San Diego, California, USA