IoT-TEG 4.0 A New Approach 4.0 for Test Event Generation
ABSTARCT :
The Industry 4.0 (I4.0) is a paradigm settled down by the introduction of the Internet of things (IoT) into the production and manufacturing environment. I4.0 promotes the connection of physical items such as sensors, devices, and enterprise assets, to each other and to the Internet. The information that flows through these items is vital because it serves to make relevant decisions. One of the main features of I4.0 is its adaptability to the human needs, this means that the items included in the I4.0 network are heterogeneous and they are large in number. The majority of I4.0 papers, which are focused on testing, describe a specific system or part of the I4.0 network. We have not found any paper that undertakes the testing of multiple connected IoT devices that will receive, process, and make decisions according to the complex and real data that travel through the network. In this article, we present IoT-TEG (Test Event Generator) 4.0, which is based on the test event generator system IoT-TEG . IoT-TEG 4.0 provides two new main contributions: the generation of test cases, which can include all the different types of data that the connected I4.0 devices under study can manage, and real-time testing. Additionally, its validation using real IoT programs is included and the results show that IoT-TEG 4.0 allows us to conduct tests that mimic real IoT system behaviors.
EXISTING SYSTEM :
? The process is also iterative in that if new information arises in one step, previous steps will be revisited, and changes will be made accordingly, like adding new use cases or reprioritizing existing ones.
? This approach starts with an analysis of existing problems in the actual (physical) processes (bottlenecks, for example).
? The IT assessment is primarily concerned with the question of how to integrate legacy systems into the IIoT platform so as to enrich data and use existing interfaces.
? With the integration of existing brownfield data sources being one of the major challenges of shopfloor digitization,considerable effort has been made by platform, software, and specialized-equipment providers to allow access to available data.
DISADVANTAGE :
? Handling human factors is a challenging problem concerning both cellular manufacturing and human-robot interaction.
? Adaptive systems are suitable to handle these problems with the help of more frequent monitoring and model adaptation functions.
? Learning the causes behind a failure can enable manufacturers to more effectively address the root of the problem, rather than its symptoms.
? Analysis enabled Schneider to address the root cause thermal expansion problems before they led to “symptoms” bearing vibration that caused equipment shutdowns.
? These issues were, in large part, rooted in a shortage of seasoned talent to train employees within the new manufacturing facilities.
PROPOSED SYSTEM :
• To implement the MVP or pilot, IBM proposes that clients leverage our MVP product method.
• To accelerate those activities, IBM proposes leveraging the industry apps contained in IBM’s suite of IoT and Watson AI solutions for industrial businesses and evaluating their coverage level to determine which use cases to implement.
• To speed up the architecture elaboration and design process, IBM proposes leveraging one of its specific intellectual property assets.
• The best IBM practice is to propose building a long-term strategic partnership in which IBM and its customers jointly deliver projects, programs and managed operations over the coming years.
ADVANTAGE :
? The increasing degree of automation also does not necessarily lead to enhanced operator performance.
? Real-time operator support and performance monitoring require accurate information concerning the activities of operators, which means all data related to operator activities should be measured, converted, analyzed, transformed into actionable knowledge and fed back to the operators.
? Intuitive displays can reduce the cost of operator intervention as the performance of the operator is improved by the auditory and visual understanding.
? Intelligent interaction space supports the operators to complete their work with high efficiency, high success rate and low burden.
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