**4.5 Issues and challenges involved in adapting quality control systems in intelligent manufacturing**

In this section challenges involved in the adapting of disruption application in intelligent manufacturing is outlined in **Table 5**. There are methods that could be used to control quality during manufacturing process [20, 21, 43] alluded that discrepancies in the document and. Process involved in manufacturing could be


*Legend: Production Manager-PM; Quality Control Officer-QCO, Production Supervisor-PS; ICT Officer-Information Communication Technology Officer.*

#### **Table 5.**

*Challenges involved in Adapting Quality Control System.*

identified and process with different method, difficulty in the choice of correct method has been a challenge from time. In the context of this study, some significant challenges were profiled and processed. In relation to **Table 5**, some of the challenges profiled are stated as machine–machine interaction; man–machine interaction; data quality; cyber-security; spare part management; data acquisition/ storage; training challenges and testing cost and complexity.

The respondents' opinion sample in this context about the challenges include that of production manager, quality control officer, production supervisors and ICT officers. The challenges are ranked in the appropriate order; machine–machine interaction, man–machine interaction, data quality, cyber-security, spare part management, data acquisition/storage, training challenges and testing cost & complexity. The production managers. ICT officers and Production supervisors ranked challenge of machine–machine interaction and man–machine interaction as 1st of the challenges; similarly, the same category of the managers ranked the same parameters 2nd according to the previous order. PS and ICO ranked data security and cyber security 3rd among other factors. Data quality was ranked 4th alongside Cyber security and data quality while data acquisition/storage; training challenges and testing cost and complexity were ranked 5th, 6th and 7th respectively by all categories of managers. Quality tools like Pareto diagram, Ishikawa diagram, Histogram, check-list, Flow chart and Control charts. However, statistical quality control method has been an age long method of quality control and this could be carried out with the aid of sample analysis, application of control charts and adoption of corrective measures.
