By Sophie Dulhunty at October 30 2018 01:06:11
In the last years some organizations have emerged with the aim of creating professional communities around specific disciplines such as Software Development (SEI, ESI, etc...), Project Management (PMI), Business Process Management (BPMI), IT Service Management (ITSMF), etc... One of the objectives of these groups is to develop a body of knowledge that compiles the discipline's best practices in the form of reference frameworks, methodologies and maturity models. These assets should be considered by any organization interested in knowledge process management.
Initially, the basic rice cultivation process requires the complete preparation for the technological projects and the set-up of the milling plant. Many layouts, specifications, selection of appropriate milling equipments and units are planned for the efficient running of the milling industry. Further the assessment reports are also prepared keeping in mind the benefits with the selection of experienced personnel. There are different types of methods used in the rice milling industries. In the earlier days, conventional methods were used for paddy processing using the steel hullers and the rice processing process mentioned in the above flowchart was carried out manually.
All process instances are executed in a very similar way and it is easy to draw a flowchart detailing the sequence in which tasks are executed. It is also possible to formalize the business rules that guide decisions, normally based on the evaluation of some process variables. But recently other kinds of processes have caught the attention of process management specialists. They are known as knowledge processes, or knowledge-based processes. Knowledge processes can be defined as "high added value processes in which the achievement of goals is highly dependent on the skills, knowledge and experience of the people carrying them out". Some examples could be management, R&D, or new product development processes.
The possibility of developing some such artifact has intrigued human beings since ancient times. With the growth of modern science, the search for AI has taken two major directions: psychological and physiological research into the nature of human thought, and the technological development of increasingly sophisticated computing systems. In the latter sense, the term AI has been applied to computer systems and programs capable of performing tasks more complex than straightforward programming, although still far from the realm of actual thought. The most important fields of research in this area are information processing, pattern recognition, game-playing computers, and applied fields such as medical diagnosis.