India can see a quantum leap in the manufacturing sector only if it keeps abreast of latest technologies | The transformation of the manufacturing sector has begun. Internet of things is the next big thing for industrial enterprises and is all about being collaborative. The industrial internet revolution is taking place due to the convergence of the automated industrial system with the power of advanced computing, analytics, lowcost sensing and new levels of connectivity permitted by the internet.
The deeper interlocking of the digital world with the world of machines holds the potential to transform the global industry, and in turn many aspects of daily life, including the way many of us do our routine tasks.
Big Data, mobility, cloud, analytics, and smart machines contribute to the concept of being connected. These technologies result in zero downtimes, improved profitability, enhanced productivity and optimised resource utilisation. The machines become part of an intelligent network that can automate information and action to optimise plant floor performance.
There are four main parts to the Industrial IoT: intelligent assets with sensors, processors, memory, and communications capability; data communications and infrastructure; software and analytics; and people and business entities that use the technologies for better decision making and improved business processes and models. To that end, the promise of this technology will change manufacturing in the following ways:
Big Data is a software, facilitated by all that the internet brings to the table that can harness the details created from processes, and turn that data into knowledge. This plays a vital role in decision making and transformational technologies such as analytics, mobility and others. With advanced analytics, users can get Big Data from anywhere and everywhere and can perform massive calculations, complex algorithms, and analysis for faster decision making.
Smartphones and tablets have entered the shopfloors too and provide workers with the latest information at their fingertips. For example, maintenance workers could have work orders, repair instructions, and spare parts availability and ordering capabilities and the like on their handsets. Operators will have real-time plant operating information and the executives a rollup performance information and drill-down capabilities. For all of these, using mobile devices allows access to information at the point of need, without requiring the user to return to a desk or central location.
In addition, apps to speed machine setup are already available. Implementing and supporting this can be challenging for IT and typically involves the use of a mobile device management (MDM) platform. These platforms can typically support multiple types of devices securely; manage the devices; and help create, manage, and deploy applications.
Wi-Fi and other Internet technologies are increasingly necessary to support mobile devices and new sensor connectivity. As production assets are equipped with more sensors, together with local intelligence and communications capability, robust, secure Wi-Fi and Ethernet connectivity are increasingly important. For a certain class of asset information (for non-control purposes), Wi-Fi can be the most cost-effective means to communicate with predictive maintenance or other systems. The technology is feasible, available, and widely installed today.
Manufacturers should consider cloud computing as an optimum and less expensive solution to meet their needs. The cloud allows free knowledge sharing so that others don’t have to reinvent the wheel. Benefiting from each other’s work reduces mistakes and improves productivity.
The cloud can not only dramatically increase productivity but also speed learning by offering a cadre of application tools – everything from re-useable machine control algorithms to previously established troubleshooting and diagnoses, or simulations for production scenarios. Manufacturers could also use it to compare line performance, therefore becoming a repository of best practices.
As investments in the networks and systems that collect, manage, deliver and store this data increase, so does the expected computing power to deliver the value of the information through analytics. With the data storage and processing needs increasing, in-memory solutions can provide the needed speed and performance to handle massive datasets and intense calculations.
Today, many applications have been rewritten and optimised for in-memory servers. These servers can power on-premise or cloud-based solutions. In-memory technology, together with cloud computing, analytics and Big Data, will be useful as smarter, connected assets are deployed.
Sensor technologies too have evolved considerably. A couple of technologies like 3D vision and laser scanning are being increasingly deployed in organisations. For 3D vision the dominant sector of the market is primarily in small piece parts that have relatively short machining cycle times.
3D laser scanning, however, which is faster and less expensive to deploy, is also becoming a viable alternative to stereoscopic vision systems in these applications. It is used in conjunction with CAD/CAM systems and can be applied to simulate machining operations. Furthermore, when drawings are not available, the technology is also useful for reverse engineering in conjunction with CAD systems to refine the dimensional qualities of the model.
Today, digital manufacturing (DM) technologies allow controls engineers to virtually design and build in 3D the mechanical, electrical, and controls components that comprise a new production system. The virtual commissioning (VC) here eliminates many of the time and resource consuming tasks that engineers would otherwise have to perform on real physical equipment before it can be used.
Not only does this process significantly reduce the product launch lifecycle, it allows engineers to optimise these processes before they are physically installed. By integrating the digital product design with the virtually design manufacturing environment, it is possible to modify either the product or the production process/equipment without incurring prohibitive costs or delays. VC involves the creation of a model that represents an accurate and realistic 3D simulation of mechanical, electrical, and control systems to validate the physical functions of a production system prior to actual physical implementation.
The inherent complexity of integrating mechanical, electrical, and control systems has necessitated a rather labour-intensive commissioning process typically carried out by a team of engineers and technicians to physically test, validate, and ultimately bring the production system into operation. VC can greatly reduce or eliminate the need for physical commissioning, reducing requirements for engineering resources, shortening time to product launch and reducing costs.
The printing of parts and products has the potential to transform manufacturing simply because it lowers the cost of fabrication and material while allowing manufacturers to reduce the risk of large production runs. In a world, where economies of scale matter less and mass-producing parts in large production runs is not economically feasible in a rapidly changing market, 3D printing will allow for affordable customisation and manufacture to order.
When it comes to simulation, today’s PLM providers offer CAD tools for product design and CAE tools (FEA, CFD, multi-physics) for product testing. Additionally, they offer systems engineering solutions that provide virtual (3D) modeling tools. Placing 3D product models in a virtual environment enables developers to simulate, verify, and validate the actual physical behaviour of the product.
This allows the system to take gravity, friction, and other physical characteristics into consideration to calculate and understand machine behaviour. Additionally, it provides a means to validate the functional component interaction of the device based on the systems engineering functional decomposition and model-based design.
A notable trend in condition monitoring is the growth of remote services by asset vendors. This is fueled by manufacturers’ willingness to share real-time, in-service asset performance data streams with the asset vendors or other third parties. By establishing “digital umbilical cords” to a number of in-service products across a range of end users, machine vendors can spot potential failures and performance issues in advance, so maintenance activities can be scheduled to minimise unplanned downtime.
Thus, the manufacturing sector is witnessing an explosion of technological changes. For one to leapfrog to the next level and adapt to this transformation would require a change in mindset and the willingness to learn and update themselves.
Sharada Prahladrao
Editor & Public Relations Manager
ARC Advisory Group, India