Manufacturing

Trends and innovations
Technological advancements in the manufacturing sector play a vital role in the growth of the world economy. New manufacturing trends include innovations that aim to improve the productivity and sustainability of the entire production process. The major innovation trends in the manufacturing industry are process automation, additive manufacturing, and the use of artificial intelligence (AI).
    However, in the aftermath of the COVID-19 pandemic manufacturing companies are also focusing on ways to maintain productivity with a reduced manpower following social distancing norms. Hence, developing smart sensors, immersive technology gadgets, and wearables that eliminate the need for the physical presence of workers. Simultaneously, companies are shifting to sustainable material and green energy sources to reduce the carbon footprint of manufacturing.

Impact Of Manufacturing Trends
    Although the COVID-19 pandemic made progress in manufacturing economies sluggish, the establishment of a new normal has boosted the demand for finished products around the world. The current situation makes manufacturing companies invest time and money on technological innovations that reduce lead time and resource wastage and ensure maximum uptime. Tackling these challenges predominantly through solutions that implement process automation and AI-based decision-making systems.
    In addition, innovations in the application of Industrial Internet of Things (IIoT) and immersive technologies aid remote monitoring and maintenance of industrial assets. Additive manufacturing is also gaining a foothold in the manufacturing ecosystem due to innovations that transform it from a prototyping tool to a mass production process with endless possibilities of customisation.

Industrial Automation
    Since the first industrial revolution, all process and equipment improvements aim to implement some degree of automation. The reduction of human involvement in repetitive and hazardous tasks makes the production line more productive and safer. But the cost and complexity of such automated equipment increase exponentially with the level of automation. However, recent innovations in control systems and robotic technology make the implementation of automation ideas easy and more cost-effective. This makes robotic automation the most important technology among the manufacturing trends. Automation simplifies a wide variety of processes in the production line including material handling, assembly, painting, and other machining and finishing processes.
    Provides scalable and easy-to-use intelligent material handling solutions to automate complex industrial workflow. They integrates its proprietary vision module powered by AI and 3D vision, into their autonomous mobile robots (AMRs). The vision module enables Gideon’s AMRs to see, understand, localize and navigate across indoor or outdoor environments. The cameras and built-in sensors provide data to the localisation system that creates dense 3D environmental models and updates them in real-time. This allows AMRs to operate safely alongside workers and equipment by adjusting to their movements and changing working conditions. The advanced visual perception system automates material transport, lifting and feeding, and other collaborative movements on the production line.

Additive Manufacturing
    Additive manufacturing provides an efficient and quick method for converting a concept into the final product. The rise of computer-aided designing has taken away the limitations in product design and additive manufacturing breaks the barriers of traditional manufacturing techniques to materialise unconventional designs. The intricate details of these designs incur a large production cost with standard manufacturing techniques. But the current methods of additive manufacturing do not support mass production. To tackle these issues, innovations in additive manufacturing reduce the cost of transition from traditional manufacturing processes. The implementation of this manufacturing trend also provides the opportunity for mass customisation, distributed manufacturing, and on-demand production.
    Specialises in 3D printing of high-performance polymer. The Nematic 3D printing technology creates high-performance end-use parts which are superior to the current benchmarks in 3D printing. The technology uses liquid crystal polymer (LCP) as reinforcements in the polymer matrix which provides high inertness and fire resistance and is easier to recycle than carbon fiber. In addition, LCP undercuts carbon fiber manufacturing with a low raw material cost. This makes it suitable for manufacturing high-end parts for the aerospace, medical, and electronics industries. They integrate the technology into a retrofit 3D printer head simplifying its adoption into existing machinery. 

Artificial Intelligence
    Modern manufacturing equipment provides companies a multitude of data that includes process and performance parameters. Proper analysis of this data provides insights on production optimisation, maintenance scheduling, and asset management. Manual processing of these data is time-consuming, and simple computer software is unable to recognise trends and infer logical conclusions. Here, artificial intelligence (AI) is an evolving technology among the manufacturing trends that solves the problem of analysing vast amounts of data and getting valuable insights. AI improves many aspects of manufacturing operations like inventory management, supply chain visibility, warehousing cost reduction, asset tracking, forecasting accuracy, transportation cost reduction, and quality management. Another crucial application of AI is predictive maintenance which ensures manufacturing companies operate with minimal or zero unplanned shutdowns.
    Provides new products and services in the area of AI. ZeoAnalyzer is AI-based product that enables predictive maintenance of industrial equipment and assets. The software performs stream analytics of machine data from IoT sensors and identifies indications of failure and degradation in performance. The platform uses this information to send reports and alerts to maintenance managers regarding time to failure, regular maintenance of parts, and simultaneously communicate with ERP systems for spare part details. In this way, ZeoAnalyzer helps companies reduce maintenance costs and increase the productivity of machines.

Industrial Internet of Things
    Programmable logic controllers (PLC) and human-machine interfaces (HMI) display all the data regarding the machine condition and also enable changes in machine settings. But these units require physical presence to capture the relevant information and make the necessary adjustments. This restricts the visibility of the production unit to the shop floor employees. Industrial internet of things (IIoT) through its interconnected sensors, instruments, and other devices connects the top management to the shopfloor enabling fast decision making. This makes IIoT one of the manufacturing trends that streamlines operations, saving money, and improving safety. In combination with AI technology IIoT also allows companies to build digital twins of their production lines. This gives companies information regarding the shopfloor events and the condition of machines.
    Developing IIoT platforms that connect companies to their machines. The solution aids to visualise, analyse and act effectively on the performance of the factory. Viga Lab uses their sensors that are compatible with both digital and analog machines, to monitor if machines are operating and at what capacity. The software provides a web platform, a SCADA (Supervisory Control and Data Acquisition), and a mobile application to operate and visualise the connected factory. The solution thus enables managers and engineers to view the factory performance remotely from a computer or a smartphone.

Immersive Technology
    A variety of assembly processes still depend on a human workforce due to the degree of flexibility required for the procedure. This adds to the factor of human error in manufacturing. Although instruction manuals and quality standards are physically available to always refer them in an active assembly line is impractical, increasing the probability of errors. Immersive techniques like augmented reality (AR) convert the manuals into digital content that overlays on a piece of machinery and guides the operator, helping to identify and fix any problems. AR has the ability to render 3D visuals of machines in actual proportion, training the operators through step-by-step visuals on how to repair and maintain machinery. Immersive technology also allows skilled workers to carry out maintenance remotely, hence reducing the skill gap making it a clever technology among the other manufacturing trends. In addition, virtual reality (VR) technology supports the virtual prototyping of products.
    Developing a 3D real-time collaborative visualisation software for industrial applications. Weviz VR is a virtual prototyping tool that creates 1:1 VR models that help to validate the design and ensure ergonomics before going into production. Weviz Review is a real-time review platform where the design team is able to collaborate with stakeholders like the manufacturing and marketing team, using virtual models. Weviz Studio is the software that renders the validation and reviews models in real-time with realistic materials, mechanical constraints, and realistic lighting conditions. All these solutions avoid the build of extra prototypes for validation, reducing the product development cost.

Big Data
    From supply chain management to maintenance scheduling the process of capturing and storing data is critical to ensure agility in the manufacturing system. The data in a manufacturing company consists of information regarding assets, materials, processes, and customer feedback all in different formats and protocols. For this myriad of data, the conventional methods of data handling are inefficient in performing predictive and advanced analytics. Here big data analytics systems with machine learning algorithms are one of the manufacturing trends that finds patterns and provides real-time insights. The vast amount of data that these analytics platforms process improves safety, enhances efficiency, simplifies product innovations, and reduces costs to a greater extent.
    Big data analytics to simplify the decision-making process of complex production processes. The software uses data from multiple sources and consolidates it to visualise, compare and evaluate them. The solution finds relationships between input data (e.g. material data or machine parameters) and quality features of the product, which enables process improvements. The AI algorithms of the big data platform generate predictive models that intelligently control the process. The proactive interventions from the solution help manufacturing companies prevent rejections and machine downtime.

Cloud Computing
    The data that IoT devices collect from production lines have great potential to transform manufacturing operations. In the traditional system, all the data handling and analysis activities take place through the in-house hardware and servers. This adds the cost of setting up and maintaining expensive IT infrastructure and also restricts the accessibility of data to remote workforces. Cloud-based systems avoid the need for costly computer hardware and servers and allow the sharing of data over a wider platform. Cloud computing is one of the well-established manufacturing trends that enables on-premises users and remote workforces to collaborate in real-time effectively. The cloud approach in manufacturing is faster, improves manageability, and reduces maintenance.
    An API (Application Programming Interface) that connects all the components of a distributed cloud infrastructure. The platform enables interoperability with any hybrid or multi-cloud compute environment. Ridge cloud’s solution enables facilities in diverse locations to all have reliable, low-latency connectivity to the cloud. The massively distributed infrastructure of Ridge cloud ensures multi-site manufacturing companies have their resources available even in the most remote locations. Thus, the solution overcomes the challenges of data and knowledge sharing in multi-site manufacturing.

5G
    The implementation of IIoT needs a fast, secure, and continuous connectivity between the different devices in the manufacturing system. The increase in the number of connected devices and the compounding of data creation and utilisation constantly intensifies the demand for bandwidth. In this situation, the latest generation of network technology, 5G (mmWave) satisfies the need for high speed, reliable and secure connectivity. The 5G network’s high capacity, wireless flexibility, and low-latency performance enable companies to set up smart factories that greatly rely on sensor technology. This manufacturing trend features connected tools, utilising data to guide the tasks of the workforce.
    Developing devices that help to set up private 5G networks in various scenarios like smart factories, buildings etc. The Qucell Indoor mmWave module supports mmWave and delivers high-performance indoor wireless service enabling low-latency and high bandwidth data transfer. This expedites manufacturing technologies in smart factories demanding real-time computing. HeMS is another offering from Qucell which is a fully automated management system for the fast roll-out and easy self-configuration of smart cell networks. HeMs also has an easy and flexible interface for monitoring and management of smart cells. The Qucell solution also reduces capital expenditure with better coverage avoiding the need for extra cells.

Wearables
    Like machines, the human workforce is an important asset of manufacturing companies. So the monitoring and coordination of the employees is an unavoidable aspect of optimising productivity. Wearable devices like smartwatches, smart bands, headsets provide critical data quickly and unobtrusively. The manufacturing trends of wearables improve the safety of workers by constantly monitoring movements on the shop floor and raising alarms in the event of a safety incident. The monitoring of shop floor movement also provides data that is useful in process improvements and layout designs. These solutions provide the companies with the health conditions of workers facilitating the better care of employees. In addition, wearable headsets incorporated with AR blend real-world views with software-driven overlays to instruct workers on the factory floor.
    Providing solutions for analysing the motion of workers for process optimisation. Motion-Mining enables automatic and anonymous analysis of manual work processes with regard to their ergonomics and efficiency. These wearables on the employees’ wrists or waists anonymously record various activities. Theyalso provides tracers and beacons permitting location-based analysis of the contacts to uncover critical areas. Motion Miner’s AI software automatically analyses the data using deep learning algorithms and helps to optimise the waiting, travel, and handling time in processes in the shopfloor. The platform also analyses the ergonomics of the processes by detecting unhealthy stooping, overhead work, or walking distances. The analytics dashboard also acts as an infection prevention tool by identifying contact hotspots on the factory floor.

Green Manufacturing
    The rise of global temperatures is directly related to each phase in the industrial revolution. The unchecked setup of manufacturing units and the wasteful use of resources in the growing phase of each industrial revolution has done irreversible damage to the planet. Thus, the fourth industrial revolution of smart technologies does not have a free pass to utilise resources. This is why manufacturing companies are shifting to sustainable materials, energy, and processes to reduce their impact on the environment, making green technologies important among the manufacturing trends. These sustainable solutions make the final product green ensuring a longer lifetime and recyclability.
    Using additive manufacturing of high-performance materials to create more sustainable products. They use its structured development strategy for selecting the right modeling, the right material, and the right printing process for manufacturing companies. The material selection process evaluates materials to choose the one with high performance and durability and with a minimum impact on the environment. The effectiveness of material selection in maintaining sustainability depends on the printing process. The appropriate printing process ensures a sustainable flow in the production process. So, by taking decisions based on a green outlook 4D pioneers minimises the contribution of manufacturing to environmental pollution.