# Cognitive Manufacturing in Industry 4.0 toward Cognitive Load Reduction: A Conceptual Framework
## 1 Introduction  
Industry 4.0 (I4.0) is the mainstream name given to the Fourth Industrial Revolution introduced by the digital age. Some experts trust that Industry 4.0 is more evolutionary than revolutionary since computers were the establishment of the last revolution and remain the establishment of Industry 4.0 [1]. Different technological developments resulted in Industry 4.0. This new paradigm faces the challenge of being exceptionally computerized and financially savvy, as well as producing custom products in a large-scale manufacturing condition, and it can change the role of traditional assembly lines by altering how goods are produced and services are offered [2]. The rapid advancement of technologies such as cloud computing, big data, mobile internet [3], augmented reality (AR), virtual reality (VR), and artificial intelligence (AI) has resulted in substantial work in these areas [4]. Furthermore, the combination of these information technologies and the assembly industry has instigated the current fiercely debated issue of intelligent manufacturing (IM) [5]. Cognitive manufacturing (CM) utilizes cognitive computing, the industrial Internet of things (IIoT), and advanced analytics to upgrade manufacturing processes in manners that were not previously conceivable. It enables associations to improve major business measurements, for example, productivity, product reliability, quality, and safety, while decreasing downtime and lowering costs [6]. In 1990, [PERSON]. [7] emphasized how the cognitive imprecision of data and vulnerability in user awareness of the computing environment were significant components of human-computer interaction, which should be imprecision-tolerant take into account the inexact mode of communication. Considering this, before the time of big data, cognitive technologies were unrealistic, as their systems need data to analyze. For most manufacturers, having enough information is no longer an issue. Indeed, most manufacturers deal with more information than they can break down, leading to a use of more seasoned techniques [1]. Cognitive systems are fit for automating routine decisions, and they support Industry 4.0 by creating significant experiences that help human decisionmakers to manage anomalies or other abnormal and complex business decisions. Cognitive systems can comprehend vast quantities of factors that uncover underlying causes of issues or point to more effective courses of action [1]. The enthusiasm for cognitive aspects of human performance has drastically expanded as of late in manufacturing, supplementing the zone of physical ergonomics, and the spotlight on cognitive aspects may offer critical insights to industries. Significantly increased interest has been aimed at cognitive aspects and their impact on human performance and production outcome [8]. Although the term \"cognitive manufacturing\" has never been directly related to reducing human cognitive load in manufacturing, it is interesting to assess points where the subjects are interlinked. This paper aims to investigate what causes cognitive load reduction in manufacturing environments, i.e., technologies that reduce the identified causes and the applications of cognitive manufacturing that adopt the referred technologies. In this study, an investigation of the subject was performed through the following research question:  
RQ1: Is cognitive manufacturing a term that can be extended to a technology that reduces the human cognitive load in manufacturing? To help deconstruct the main research question, three sub-questions were developed:  
* SRQ1: What causes cognitive overload in manufacturing environments? * SRQ2: Which are the technologies that are able to reduce the cognitive load in manufacturing environments? * SRQ3: Which are the cognitive manufacturing applications that use technologies that reduce the cognitive load?