Smart Manufacturing: Brief introduction
The smart manufacturing the latest new generation manufacturing machine used in different industries for manufacturing purposes. Smart manufacturing is implemented in different industrial sectors for the increased output of the industry. With the help of smart manufacturing different tasks of the industry are mated automated. The automation of a factory as per the new technologies can be also termed as the smart manufacturing technique. Computers are mostly used in the smart manufacturing procedures to control the automatic operations of a factory or a unit of a factory. Smart manufacturing is also referred to as computer-integrated manufacturing which results in rapid design change, high-level adaptability, flexible workforce training, and digital information technology.
By implementing smart manufacturing in the industrial sector several benefits can be accomplished such as supply chain optimization, fast changes for the demanded production level, efficient recyclability and efficient production.
According to the smart manufacturing industry or a smart industry should have a multi-scale simulation, multi-scale dynamic modeling, interoperable system, good cyber security, networked sensors, and intelligent automation. An industry comprising of all the above-mentioned parameters can be considered as a smart industry possessing smart manufacturing capability.
Overall Equipment Effectiveness:
The overall equipment effectiveness method is shortly written as OEE. This is a scale to measure the different parameters utilized to increase the effectiveness of a manufacturing operation. The different parameters like time, material and facilities are involved in the analysis of the overall equipment effectiveness. OEE is used to measure or estimate the manufacturing capability of an industry. With the OEE it can be estimated how much time from the total production time of a factory is productive. This estimation is done based on different parameters. A unit showing a 100% score means that the unit is producing good parts with zero stop time and as fast as possible. In other words, this performance or the score of a plant or industry can be termed as 100% performance, 100% availability and 100% quality.
The overall equipment effectiveness of a plant should be measured often to check the performance and productivity level of the industry. Different losses and limitations of a plant can be measured and estimated by this technique which will in return increase the productivity and the profit.
Predictive maintenance is the type or a class of maintenance in which the machine data and the process evaluation are considered for the maintenance purpose. Predictive maintenance is usually used for Industry 4.0. The status data is obtained from a machine from this procedure which is used to carry out proactive maintenance on the machinery of the system. The maintenance of an industry is an essential need that should be done on every industry or a plant to maintain the productivity of the industry or to improve productivity. The overall maintenance for a factory also results in loss as the industry is closed for the maintenance for several hours or days thus affecting productivity. To avoid such downtime for a unit, the predictive maintenance is utilized. With the help of the predictive maintenance, the specific part which requires maintenance is selected for the maintenance with the help of the machine data and the process evaluation.
Connectivity of Machines, Equipment and Plants:
In a production unit a number of machines, different equipment and plants are interlinked with each other. The different things involved in the production unit should be connected in precision with each other to give better outcomes in terms of productivity. The connectivity topologies for these parameters differ from industry to industry. The modern connectivity techniques should be utilized such as the Industrial Internet of things (IIoT). IIoT controls the different equipment, machines, and plants attached to it by automation. The automation of an industry improves its productivity.
The data related to different sectors of industry are analyzed to check different parameters of an industry such as productivity, maintenance, and performance. The analysis of data for the industry is performed at different intervals of time or when some deficiency is observed in the performance of the industry. The data analysis is used to improve the performance of the industry by covering the deficiencies in different processes. The data analyzed is a useful information which is utilized again and again for the evaluation of the plant or the industry in several ways. The performance of an industry before or after an upgrade can be evaluated and so on.