An integral part of Industry 4.0, ScoutCam technology provides efficient predictive maintenance and identifies changes within condition-based monitoring.
ScoutCam is pioneering the Predictive Maintenance and Condition Based Monitoring markets with its visualization and AI platform, in the fields of Aviation, Unmanned Aerial Vehicles (UAVs), Mobility and Transportation, Energy Plants and Wind Turbines.
Today’s industrial challenges stem from the very innovations that answered the issues of the past: speeding up operational times and overall process, verifying the adherence to updated safety regulations and improved efficiency are some of the present-day challenges that necessitate the ability to identify, predict and prevent potential malfunctions within the shortest amount of time, thereby creating a streamlined process with maximum productivity and minimum downtime.
The latest stage in the ever-expanding global marketplace, Industry 4.0 includes the automation of different industrial processes, machine learning and a growing reliance on industrial IoT the Internet of Things (IoT), which is composed of the online, wireless exchange of information between devices embedded with sensor equipment. Its impact on our lives is still unfolding, as the breadth of its effects continue to shape our present and future. By providing cutting edge technology that cuts down on vehicle malfunctions rates while increasing operational time, ScoutCam’s visualizing, analyzing and predicting solutions constitute a significant contribution to the currently developing Fourth Industrial Revolution.
The Fourth Industrial Revolution, or Industry4.0, is looking to utilize any and all relevant technological advancements, in order to optimize as much of the operational process as possible, providing greater cost-efficiency and increasing companies’ return on investment. First arising during the early 21 Century, Industry4.0 melds together cutting edge advancements from different industries, to successfully predict the needs of both the end client and the overarching operations process, aiming to meet their individual pain points.
The innovations that make up Industry4.0 also include computer software and hardware, human-to-machine and machine-to-machine interactions, computational algorithms, artificial intelligence (AI), augmented reality (AR), robotics, three-dimensional printing and genetic engineering.
Cyber Physical Systems,
internet of things,
Moving from the handmade production of goods to steam and water-powered machinery, as well as man-operated assembly lines, the First Industrial Revolution took place in the U.S. and Europe during the 18th and 19th centuries.
Spanning from the end of the 19th Century until the beginning of the 20th Century, the Second (or Technological) Industrial Revolution was marked by the transfer of people and ideas. During this period, vast railway, telegraph and electrical networks were developed.
Focused on digitization of the manufacturing process, the Third (or Digital) Revolution largely took place during the end of the 20th Century. This move toward a widespread reliance on computers and the internet offered greater efficiency of entire industrial processes, with more advanced oversight, data storage and communication options.
or Industry 4.0, first arose during the early 21 Century. It aims to meld together cutting edge advancements from different industries, such as artificial intelligence (AI), machine learning and the Internet of Things (IoT), to successfully predict the needs of both the end client and the overarching operations process, aiming to meet their individual pain points.
Among their key aspects, Industry4.0 technologies are able to offer statistical calculations regarding the maintenance that are crucial for a cost-effective process and operational. More specifically, preventative maintenance helps avoid malfunctions and wear-and-tear, by relying on an ongoing inspection process that helps establish an upkeep schedule and addresses technical concerns that can arise.
A central component of predictive maintenance is condition-based monitoring (or CBM). By identifying a significant change in the way a certain critical component operates, CBM can highlight a potentially developing fault within its operations, before reaching the point when an immediate solution is necessary.
Together, the different elements of Industry4.0 maintenance offer clients the ability to optimize their operational time and overall efficiency, prevent malfunctions and reduce unplanned downtime, pinpoint possible features that may need repair, cut costs, achieve optimal quality assurance, increase profits, improve the speed with which sensor data information is delivered, minimize communication lag time, and maximize automation.
ScoutCam’s contribution to predictive maintenance in Industry 4.0 reaches across different fields, helping companies push the boundaries of what is possible to achieve. Its ability to withstand the harshest of environments, as well as the development of micro-cameras solutions, offers visualization problem-solving options that are able to fit into the tiniest of crevices and withstand the harshest of terrains. This allows the examination of the various parts and components that make up complex systems and machinery, collecting crucial data on the real-time operation process.
By relaying such information via the IoT, ScoutCam’s Locomotive visualization equipment provides its own, unique contribution to condition-based monitoring and predictive maintenance at large. Targeting possible breakdowns in the system by identifying abnormalities in its functioning helps stave off potentially enormous failures before they happen. Receiving important images through ScoutCam’s cameras and supplementary technology allows efficient machine learning to take place, and provides companies with the ability to effectively perform regular equipment life cycle maintenance, thereby making it possible to notice indicators of a potential problem and address them before they grow into a significant defect.
Routine aviation inspections form a central component in assessing its airworthiness, helping ensure the safety of the passengers, crew and cargo held inside an aircraft or any other aviation tool of transportation. ScoutCam’s visualizing, analyzing, And predicting solutions make such safety measures possible, with high-definition visualization that manages to carry out condition-based monitoring, including the collection of critical information from the aircraft, storing said data, analyzing it and offering recommendations based on the obtained information.
Utilizing predictive visualization solutions can cut costs and maximize the efficiency of complex energy-providing systems. In a move that translates into cost-effectiveness and greater sustainability, ScoutCam’s predictive maintenance technology prevents unnecessary spending on avoidable malfunctions, by accessing hard-to-reach, remote facilities such as offshore and air turbine locations, noticing any irregularities within their systems, alerting oversight and issuing a preemptive response that intercepts such potential failures before they are able to take a toll.
Assuring a glitch-free operating process is an integral part of any quality assurance procedure. And when it comes to the automotive industry, and the heavy machinery and transportation vehicles that make up its operations, the need for implementing cutting edge visualization technology that is able to significantly cut costs. By providing essential predictive data, ScoutCam’s visualizing, analyzing, and predicting solutions is able to identify potential problems within cargo transports, sensitive locomotive components and subsystems, transportation fleets and more, uncovering issues of concern and delivering important data analytics that allows for efficient machine learning and targeted problem-solving, all of which can translate into advantageous savings of both time and money.