Hyperautomation in Manufacturing

Hyperautomation in Manufacturing

Did you know that you can integrate technologies such as Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Process Mining, and Data analytics all at once into your manufacturing operations? NuMantra’s Hyperautomation platform helps you do just that. It’s a cloud platform that empowers, optimizes, and transforms your manufacturing processes and assists in making data-driven decisions.

What is Hyperautomation in Manufacturing?

Hyperautomation is a capability that is achieved by the integration of technologies such as Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Process Mining, and data analytics to automate major processes and operations across manufacturing & supply chain operations.


Hyperautomation streamlines workflows by automating time-consuming and repetitive tasks and minimizing disruptions in the manufacturing supply chain. This data-driven approach empowers manufacturers to make informed decisions and optimize their supply chain management. They can also easily monitor the health of their manufacturing processes and analyze potential issues before they lead to downtime.

Future of Hyperautomation in Manufacturing

RPA Revolution


Implementing HyperAutomation in your manufacturing business can be a transformative step if you still rely on whiteboards and spreadsheets. Technologies such as RPA, Advanced robotic systems, Machine learning & AI will collaborate seamlessly with humans in carrying out more complex tasks in less time. Moreover, RPA bots can be programmed to automatically validate the data and enter it into a system and update this data as per requirements.


Organizations that use such modern technologies will garner several benefits, including improved quality, increased productivity, enhanced decision-making capabilities, and optimized supply chain operations. RPA and AI will be pivotal in creating a more agile, digitally-driven, and  future-ready manufacturing world.

Process Mining will Reshape Manufacturing


Process Mining will be more transformative in manufacturing processes by addressing emerging challenges quickly. Process Mining in manufacturing is expected to see a seamless integration with Industry 4.0 technologies, advanced analytics, real-time capabilities, and a focus on addressing emerging challenges.


Manufacturers using these technologies will be able to predict and achieve higher efficiency, agility, and sustainability levels in their operations. Advanced Analytics and Machine Learning capabilities will enable them to predict process deviations, gain valuable insights, and optimize operations proactively. Moreover, blockchain integration, customization, autonomous process optimization, and cross-organizational process collaboration will evolve to create a sustainable manufacturing environment.

End-to-End Connectivity for Seamless Integration


Hyperautomation is predicted to reshape end-to-end connectivity in the manufacturing industry by creating a more efficient and interconnected ecosystem. It will improve automation, communication, and data exchange across the entire manufacturing process, leading to competitiveness and enhanced productivity. From supply-chain management to production processes, all interconnected systems will be capable of sharing real-time data.


Fueled by accelerated scalability, interconnected platforms, and implementation speed, Hyperautomation emerges as the upcoming frontier poised to serve as a comprehensive solution for global organizations. The essence of Hyperautomation lies in the integration of diverse technologies, mirroring the collaborative approach of humans to evolve and conquer individual limitations.

Benefits of Hyperautomation in Manufacturing Industry


Hyperautomation in the manufacturing industry brings several transformative advantages, such as faster time-to-market, increased productivity, and error-free and consistent production to gain a competitive edge. Some of the top benefits of Hyperautomation in the manufacturing industry include:


Enhanced Efficiency and Productivity


Hyperautomation helps businesses easily streamline their manufacturing processes by leveraging technologies such as Robotic Process Automation (RPA), Artificial Intelligence (AI), and Machine Learning (ML). It helps in minimizing manual intervention, optimizing workflows, and boosting overall productivity and efficiency, leading to a quick and affordable manufacturing process.


Better inventory management


Keeping track of a large inventory is always a time-consuming task. Even a minor congestion can negatively affect the business’s overall revenue, growth, and productivity. Fortunately, enormous volumes of monotonous processes can be managed and executed more accurately by Hyperautomation. It minimizes repetitive tasks, solves issues at earlier stages, and completes essential jobs more accurately.


Integrated workforce and higher productivity


Hyperautomation assists manufacturers to achieve a cohesive and integrated workforce that drives success. The combined intelligence of a digital workflow and empowered workforce enables employees to use AI to boost productivity and make better decisions.


Thus, everyone involved in the manufacturing process becomes a  part of this transformation journey. The automation of processes boosts work quality and increases employee satisfaction.


Data-Driven Decision-Making


Enabling Hyperautomation is seen as fundamental to digital transformation. It provides businesses with data-driven decision-making and efficiency as it enables the powerful combination of machine learning, packaged software, and automation techniques, than just automating processes.


This integration facilitates data and business transformation, enabling strategic decision-making and extracting valuable insights and patterns from large datasets.


Root Cause Analysis


Manufacturing quality can be enhanced in two ways: by detecting defects and by identifying the source of these defects in the manufacturing process. Traditional root cause analysis approaches include fishbone diagrams, Pareto analysis, etc. While these remain necessary tools for experts, they also need experience and knowledge to be utilized effectively.


This showcases a big problem for manufacturing businesses worrying about finding the best people. Here, Hyperautomation speeds up and improves manufacturing with machine learning and artificial intelligence. The entire process is tracked real-time, allowing engineers to intervene and enhance the process to avoid rework and manual processing.

How Hyperautomation Works in the Manufacturing Industry?


Hyperautomation in the manufacturing industry works by integrating several  technologies. You can achieve Hyperautomation with the below methodologies:

Technological Integration


Hyperautomation in manufacturing combines technologies such as AI, RPA, and IoT, creating a synergistic ecosystem. It works as a collaborative approach to enhance and automate the manufacturing processes. This form of integration streamlines manufacturing and makes it adaptable to all businesses.

Robotic Process Automation (RPA) 


The process begins by identifying manual and repetitive tasks. Robotic Process Automation (RPA) precision automates these tasks, ensuring accuracy, efficiency, and reduced human intervention in manufacturing workflows.

AI-Powered Decision-Making 


Artificial Intelligence (AI) empowers users with intelligent and robust decision-making. AI algorithms analyze data and optimize resource allocation through data-driven and strategic decisions. Implementing tools such as AI/ML will lead to future growth and enhancements.

IoT Connectivity and Real-Time Insights


The Internet of Things (IoT) creates an interconnected manufacturing ecosystem, enabling real-time data monitoring in manufacturing processes. This connectivity brings crucial insights, facilitates immediate responses to changing environments, and fosters an automation approach to modern challenges. With these promising technologies, implementing IoT gets you real-time insights and transforms the manufacturing process.

Predictive Analytics for Proactive Maintenance


Hyperautomation enables the use of analytical tools to identify & predict potential issues before they occur. This proactive approach minimizes downtime, as manufacturing systems can easily analyze data to identify and resolve the disruptions before they impact. NuMantra’s Hyperautomation approach reduces operational risks and gains deeper industry insights.

Continuous Monitoring and Adaptability


Manufacturers can leverage the huge potential of Hyperautomation with continuous monitoring and adaptive optimization. Data is generated during the manufacturing process at different workstations where products are monitored and processed through Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Process Mining, and data analytics. It specifies, analyzes, and improves productivity.

Process of Hyperautomation in Manufacturing Industry


Once you have identified the areas where Hyperautomation could be implemented, the next step involves a series of thoughtfully carried implementations of the right technologies into the existing processes .


  1. Integrating Advanced Technologies

Hyperautomation in manufacturing starts with the rapid and seamless integration of cutting-edge technologies, such as Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Process Mining, and data analytics. NuMantra offers all these tools and technologies on its Hyperautomation platform and helps businesses achieve unparalleled business outcomes.


  1. Process mining and Data Analytics

Process mining  and Data Analytics are technologies crucial for organizations to realize Hyperautomation capabilities, leading to well-informed decision making. The system collects and analyzes all data from different stages of manufacturing, structuring valuable data insights in an easily digestible digital format.

The process mining and data-driven approach assist decision-makers in better understanding manufacturing trends and resource allocation to enhance overall efficiency.


  1. Leveraging Automation

Implementation of robotic process automation can streamline the workflows in your manufacturing process. It identifies and minimizes repetitive and time-consuming tasks. NuMantra’s Hyperautomation tools can help you automate rule-based tasks and minimize manual intervention.


  1. Implementing AI and ML Continuous Monitoring

AI and ML technologies enable the continuous monitoring and learning of processes & data structures, crucial to Hyperautomation. The continuous monitoring and updates to models, improve automation quality as the system makes the required adjustments, when needed. The tools incorporate  feedback and adapt to the changes required to improve the manufacturing dynamics.

Use Cases of NuMantra’s Hyperautomation in Manufacturing Industry



  • Order Processing

NuMantra’s Hyperautomation implements RPA in order processing for automating and updating inventory systems, reducing errors, and accelerating order fulfillment.


  • Supply Chain Management

RPA is applied to improve and optimize supply chain processes, automating tasks such as supplier communication, demand forecasting, and inventory management.


  • Quality Control

NuMantra’s RPA and computer vision through its Hyperautomation platform can significantly streamline quality control by inspecting visual aspects of products, automating the analysis of product specifications, and reducing the chances of defective products passing quality checks.


  • Billing and Invoice Automation

Hyperautomation’s technologies are used for automating invoice billing and processing tasks. Automation in this area minimizes invoicing errors and manual efforts while boosting payment cycles.


  • Employees’ Onboarding and Training

Hyperautomation in manufacturing organizations can be used for smoother employee onboarding and training processes. This includes setting up accounts, automating paperwork, and delivering training materials.


Process Mining in Manufacturing


  • Production Workflow Optimization

NuMantra’s process mining approach applies algorithms to analyze and visualize the manufacturing process, identify bottlenecks, reduce lead times, and enhance overall production efficiency.


  • Quality Assurance and Defect Analysis

Process mining tools can help manufacturers track and analyze the production line, which facilitates and improves the quality control process and minimizes faulty products.


  • Supply Chain Improvement

Process mining through NuMantra’s hyperautomation platform offers valuable insights to help manufacturers identify areas for improvement, eliminate bottlenecks to optimize logistics, and enhance collaboration.


  • Analysis For Downtime

Manufacturers use NuMantra’s Hyperautomation to analyze related data, identify root causes of problems, implement preventive measures, and reduce downtime in the manufacturing process.


  • Continuous Improvement Initiatives

Process mining offers continuous improvement by providing a data-driven approach to refine old-school manufacturing processes.


  • Optimizing Resource Allocation

NuMantra’s process mining approach helps identify and optimize the areas of resource allocation, thereby reducing waste and enhancing cost-effectiveness.




  • Predictive Maintenance

Organziations are able to implements AI/ML algorithms on the NuMantra platform to predict equipment failures before they occur. It enables manufacturers to schedule maintenance activities proactively and reduce downtime.


  • Quality Control and Defect Analysis

NuMantra also provides the capability to integrate quality control systems with our AI/ML-powered system to quickly detect defects and resolve them to improve product quality.


  • Inventory Management and Demand Forecasting

AI/ML models on the NuMantra Hyperautomation platform helps analyze market trends and historical data to forecast inventory demand accurately. This helps optimize inventory levels and improve supply chain efficiency.


  • Efficient Energy Management

AI/ML models also analyze energy management patterns to predict optimization opportunities. It leads to reduced energy costs and makes efficient use of resources.


  • Production Planning and Scheduling

AI/ML models on the NuMantra platform can also optimize manufacturing schedules based on demand fluctuations and resource availability based on real-time data.


  • Collaboration of Human-Robot

AI/ML models enable the collaboration between humans and robots in the manufacturing industry. Robots can enhance human efficiency and flexibility in production processes.


BI and Analytics


  • KPI Tracking and Performance Monitoring

NuMantra’s Hyperautomation platform enables the integration of data from disparate sources and its analytics tools provides the Business Intelligence (BI) to improve production efficiency and monitor key performance indicators (KPIs) in real time.


  • Visibility of Supply Chain

BI tools assist manufacturers in increasing visibility into the supply chain, making better decisions and enhancing inventory management.


  • Quality Analytics

NuMantra’s BI and analytics tools are used to analyze data related to product quality and make informed decisions to reduce defects and improve quality.


  • Analysis Of Energy Consumption

They also assist manufacturers in assessing and analyzing energy consumption patterns during the entire manufacturing process. It helps to reduce costs, increase energy efficiency, and achieve sustainability.


  • Customer Satisfaction Analytics

Manufacturers leveraging NuMantra’s BI and analytics get insights on product performance, customer feedback, and market trends, which helps increase customer satisfaction.


Examples of Hyperautomation in Manufacturing

Assembly Line Automation 


A good example of Hyperautomation in manufacturing is using RPA, AI, ML, and NLP to automate tasks that enable the assembly of products on manufacturing lines, increasing efficiency and reducing human error. Leveraging AI capabilities, intelligent automation of repetitive tasks within packaging, material handling, and assembly processes can be enabled, which reduce the need for human intervention & errors.

Predictive Maintenance


Hyperautomation analyzes machine data to predict when maintenance is required, increasing production efficiency and reducing downtime. Using real-time data collection, predictive analytics algorithms, and automation technologies on the platform, you can analyze potential issues in machinery before they occur.

Quality Control


Computer vision and pre-configured AI models on the platform can help you detect anomalies in products, reduce defective goods, and ensure consistent quality. Further, RPA bots are then scheduled to execute tasks, that may be proactive actions, such as adjusting machinery settings, etc to improve product quality.

Case Studies of Hyperautomation in Manufacturing

Precision Engineering in Manufacturing

Precision Engineering in Manufacturing


Discover how NuMantra revolutionized precise engineering and brought manufacturing success. Using NuMantra’s Hyperautomation solution with RPA, AI, ML, and NLP can enhance and improve the current engineering processes used in manufacturing, bringing higher scalability and throughput.

Reduce Operational Costs with Hyperautomation (2)

Reduce Operational Costs with Hyperautomation


Process mining provides information on all costs of a process. NuMantra’s Hyperautomation cloud platform can detect all costly activities and identify their reasons. In case the activity includes unnecessary or repetitive tasks, it allows businesses to minimize their costs and redesign their processes.

Frequently Asked Questions About Hyperautomation in Manufacturing



  1. What Industries Use Hyperautomation?


Ans. Several industries, such as healthcare, finance, manufacturing, and logistics, are leveraging the potential of Hyperautomation. The versatile integration of Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Process Mining, and data analytics makes it valuable in different industries seeking advanced data-driven decision-making, agility, and enhanced efficiency.


  1. What is Hyperautomation in Simple Words?


Ans. Hyperautomation is a comprehensive method that combines technologies such as AI, RPA, and IoT to automate, optimize, and enhance different business processes. It also streamlines workflows, improves efficiency, and leverages modern tools to achieve intelligent and profitable outcomes in diverse domains.


  1. What Problem Does Hyperautomation Solve?


Ans. Hyperautomation addresses challenges and issues related to manual, inefficient processes, repetitive tasks, and slow decision-making. Moreover, it optimizes resource allocation, minimizes errors, fosters agility, improves adaptability, solves problems related to operational inefficiencies.


  1. What is the Purpose of Hyperautomation?


Ans. Hyperautomation helps revolutionize operational processes by integrating advanced technologies such as Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Process Mining, and data analytics.

It focuses on enabling data-driven decision-making, reducing manual efforts, enhancing efficiency, and fostering adaptability. Hyperautomation assists businesses in streamlining workflows and optimizing various aspects of business processes.


  1. Why Do Businesses expect to gain from NuMantra’s Hyperautomation Platform?


Ans. NuMantra’s Hyperautomation cloud platform combines Robotic Process Automation (RPA), Artificial Intelligence (AI), Machine Learning (ML), Process Mining, and data analytics for businesses seeking to transform their operational efficiency.

The platform leverages cutting-edge technologies to enhance efficiency, automate tasks, and provide valuable insights critical to informed decision making at multiple levels. When implemented, these technologies ensure improved productivity and streamlined workflows and help businesses adapt to the changing business landscapes, making it a vital tool for modern businesses.