**5. Conclusion**

Intelligent quality management is attracting the attention of manufacturing society as it provides much opportunities to improve quality of both products and services. Agent based systems, knowledge based system, computer vision and intelligent inspection systems are proven to be capable of sustaining the quality of manufacturing systems as well as the quality of respective outputs.

As outlined in this Chapter, artificial intelligence and intelligent tools can be utilized for quality operations before, during and after manufacturing. Since each manufacturing proses is unique in terms of attributes, characteristics, and qualities products and processes. Special attention is to be given in developing intelligent quality systems. Relevant expertise and domain knowledge need to be acquired and presented to the computer for generating reasoning about the respective quality function.

Developing real-time monitoring and failure prediction systems, real time observation through visual inspection, data analysis and visualization of information which drives the evidence-based decision making and integration of the manufacturing systems throughout the whole supply chain and manufacturing life cycle could very well handled with the support of intelligent system generation technologies. This in turn supports continuous improvement of manufacturing systems in terms of reaching better quality.

The examples from the literature clearly indicates successful implementations. Sustainable quality can be better ensured with the support of intelligent tools. The manufacturers may have so many opportunities for generating fully automated quality systems with certain degree of autonomy. This definitely encourages transformation of traditional quality system to smart production system, especially when digitization process is recognized as one of the major strategic objectives.
