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Intelligent agents are the upcoming frontiers of research in process industry specially in taking managerial decisions. Agents are tasked to work in societies with other artificial peers in modes like collaborating, cooperating, and competing in order to defend their own goals and achieving them while maintaining their existence and interactions in the society. The management of resources in process industry, relationship building for collaboration with friendly or competing against rival competitors, maintaining proactive behavior within the society and innovation to discover new more effective ways to achieve their goals are pressing issues. These are computational expensive tasks.  There is a dire need to optimize the working model of the agents to make them more autonomous and intelligent in a broader social prospective. Many models of mapping human emotions in agents are available these, however, do not state how to improve the productivity of the agents. In this paper, we present a model of agents in which human emotions are mapped for agent communication and interactions. The emotions for this stage like joy, despair, envy, adventure motivation, and fear are implemented quantitatively. These emotions are employed to increase the productivity, proactive behavior, and make agents more autonomous and intelligent.  It removes the over head of managing and running separate services for management of resources in process industry.