Hybrid Process Management: A Collaborative Approach Applied to Automotive Industry

Abstract

Today, manufacturing is moving towards customer-driven and knowledge-based proactive production. Shorter product life cycles lead to increased complexity in areas such as product and process design, factory deployment and production operations. To handle this complexity, new knowledge-based methods and technologies are needed to model, simulate, optimize and monitor manufacturing systems. Existing large Enterprise Information Systems (EIS) impose structured and predictable workflow, while processes "on the ground" are often unpredictable and involve a large number of human based decisions and collaboration. This is leading to a major shift on EIS paradigm and leading to development of a set of specialized small applications, each one with fewer features, but highly specialized, flexible, cross linked and easy to use. This paper presents a hybrid management solution intended to support collaboration and decision in the scope of automotive engineering and planning. The solution, labelled as HPM - Hybrid Process Manager, encompasses a set of tools for work, information and communication management fully integrated with knowledge based engineering processes. Its overall aim is to ease the flow of information between all the partners, making it more reliable and actual, allowing a closer control and faster reaction to upcoming events. The adoption of HPM approach proves to be quite effective and efficient, leading to significant results in terms of cost and time saving. When using the solution, managers no longer need to constantly ask for reporting, leading to a significant reduction on email and paperwork. It is relevant to underline that the proposed approach allowed planners to concentrate in important issues improving the product and avoid non-value added efforts and time on collateral activities. Another main advantage stays on the experience retrieval module built in top of the solution, allowing easy access to expertise, knowledge and best practices generated by previous projects, so that they can be readily incorporated in the design of new processes as a factor of knowledge sustainability. (C) 2016 Published by Elsevier B.V.