# Cognitive Manufacturing in Industry 4.0 toward Cognitive Load Reduction: A Conceptual Framework
## 3 Results
### SRQ1: What Causes Cognitive Overload in Manufacturing Environments?
* Digital training applications help streamline the learning procedure by exhibiting data to the learner through focused, interactive modules. These applications can be designed explicitly for the assignment being referred to, so that workers can be instructed on the exact task that they will perform [17]. Industry 4.0 technologies related to training might include virtual, augmented, and smarter operators [40], whereby workers can be trained using, for example, e-learning [43], virtual reality [44], and augmented reality [45]. * Real-time analytics dashboards can help lessen the attention and energy given to pre-analysis of data by indicating expert data on the performance of humans and machines, thereby simplifying how data are gathered and introduced [17]. This can only be performed due to the use of Industry 4.0 technology such as machine learning, turning \"big data\" into \"smart data\" [46], and using AI incorporated into human-machine interfaces to support decision-making [47]. * Augmented reality (AR) reduces human errors and lightens the memory use of the operator, safely replicating the environment [47]. With AR, there is no compelling reason to change focus between the digital and physical worlds and no compelling reason to withdraw from a task to chase applicable data about what to do straight away or how to do it [30]. Augmented operators [40] have their working environment enriched by digital information, which reduces human error and improves decision-making by displaying feedback in real time [41]. * Inline quality checks allow addressing some quality issues that are extremely small and barely detectable by eye, as well as others that are the consequence of worker fatigue. Regardless of the reason, numerous quality issues are accepted due to failures in identifying them. All manufacturers have some convention for checking quality inline; however, if the workers have the correct tools, they will be able to catch more nonconformances, prompting fewer rework hours [32]. Some examples of Industry 4.0 technologies for quality checks are automated solutions [48] and machine vision systems [49; 50]. It is important to state that not only operators benefit from technologies that reduce the cognitive load; these tools are also important to anybody doing physical or intellectual work on the shop floor [32]. SRQ3: Which Are the Cognitive Manufacturing Applications That Use Technologies That Reduce the Cognitive Load? Cognitive manufacturing completely uses the data from hardware, systems, and procedures to infer significant knowledge over the whole value chain through various procedures (design, manufacture, and support activities). Cognitive manufacturing is based on the establishments of IoT and employing analytics joined with cognitive technologies [51]. From the SRQ2 above, we were able to identify the human-computer technologies that reduce the cognitive load. Below, we analyze these cognitive manufacturing applications to fulfill the purpose of this investigation and link cognitive manufacturing to a reduction in cognitive load. According to the available literature, the following cognitive manufacturing applications were identified:  
* Asset performance management (APM) frequently catches information and data that are connected with asset condition, to provide a comprehensive perspective of the performance of the asset. The data are then used for reliability analytics and asset health visualization, to help the improvement and tweaking of different asset models [52]. Companies can use cognitive APM to sense, diagnose, and communicate performance issues to lessen unwanted downtime. The application can envision a potential failure and then investigate data from important user manuals or technician logs to comprehend how a previous similar issue was resolved, using this information to prescribe explicit activities or answers to fix the issue [6]. * Process and quality improvement are represented throughout the manufacturing process.