# Comparing Modern Manufacturing Tools and Their Effect on Zero-Defect Manufacturing Strategies
## 2 Materials and Methods  
### Zero-Defect Manufacturing  
The product or production process problem is defined as: \"in case if the output from a production is out of the range of production specification and there is no sign of indication of problem found (except the case that it is out of specifications range)--the methodology can be defined as insufficient for identifying issues, and this methodology needs to be seriously improved to be able to identify the essential challenges and problems by combining and integrating data from monitoring systems (manufacturing intelligence systems) and several important analytic methods. The classical Zero-Defect manufacturing architecture is presented and defined in Figure 1.  
It might be defined as the combination and integration of the following statements into strategies of the Zero-Defect Manufacturing (ZDM) approach [1,2,5]:  
* Continuous process of quality control of production;
* Collaborative manufacturing;
* Monitoring of the key process parameters;
* Sharing of manufacturing data without media breaks along the whole supply chain;
* Measuring of an input to the production process;
* Measuring of output with automatic sorting;
* Predictive maintenance (online);
* Data management and analytics;
* Re-configuration and re-organization of production setup. Zero-defect manufacturing strategies shall be defined as a viable concept of sustainable production, but the research in this field already considers Zero-Defect Manufacturing from a different angle of perception. The industrial and academic sectors need to standardize the terminology in the Zero-Defect Manufacturing field is recognized by industry or academic or research experts. The actual study tries to provide a clear definition of Zero-Defect Manufacturing to be used across the scientific or industrial communities, thus eliminating any misunderstandings that exist [5]. Figure 1: Zero-Defect manufacturing classical architecture. \"ZDM is a holistic approach for ensuring both process and product quality by reducing defects through corrective, preventive, and predictive techniques, using mainly data-driven technologies and guaranteeing that no defective products leave the production site and reach the customer, aiming at higher manufacturing sustainability\"._[5]  
The classical Zero-Defect Manufacturing Framework is defined in Figure 2. In the beginning, two pairs in the diagram, defined as Detect-Repair and Detect-Prevent, are not totally modern. They have existed in the manufacturing domain for decades already. However, what is new, are the modern technologies that are more advanced and data-driven, enabling more efficient implementation. Many academic publications [for example, \"[PERSON]; [PERSON]; and [PERSON] Zero-defect manufacturing the approach for higher manufacturing sustainability in the era of Industry 4.0: a position paper\" mention in Section 2] refer to detect-repair as a corrective approach, which defines something happening as already faulty and requiring corrections. Nevertheless, pair: \"Detect-Prevent\" might be referred to in any publications (academic, industrial) as an approach with a preventive character, and it uses production data and information to avoid possible future defects. Nevertheless, \"predict-prevent\" is a new concept that uses production data and is an advanced data-driven pair. In almost every definition of Zero-Defect Manufacturing strategies, a \"fault\" is defined as a defect, or it can also be called the non-fulfilment of a requirement related to an intended or specified use. This concept predicts when a fault (defect) will occur in the future, enabling it to be more ahead and prevent a fault before it occurs. The strategy follows the way of thinking of 'doing things right the first time,' and the remaining two follow triggering an action after the fault (defect) appears. Strategies of Zero-Defect Manufacturing follow two similar production approaches: one is product-oriented, and the second is process-oriented.