Automation is at a saturated level for most manufacturing enterprises. While most key processes have seen some degree of automation happening thanks to the adoption of digital tools, there hasn’t been a radical change observed in performance when traditional automation approaches are retrospectively analysed today. What manufacturers need today is the adoption of hyper automation. In simple terms, hyper automation is an automation approach defined by its ability to leverage emerging technologies such as artificial intelligence, Internet of Things, machine learning, data analytics, etc, to drive autonomous execution of critical manufacturing initiatives without human intervention.
What are the key benefits of hyper automation in manufacturing?
Streamline production workflows
Manufacturers often leverage a complex web of repetitive processes across different departments, such as inventory, supply chain, procurement, and quality assurance. Etc. Excessive manual workflows in these departments often lead to inefficiencies in the production cycle, leading to missed deadlines and unhappy customers. The processes involve both back-end managerial workflows and on-the-floor industrial cycles, and delays at either end will cause severe disruptions in business.
With hyper automation, this challenge can be easily resolved. Complex workflows at the backend can be automated using solutions like RPA, and those that involve decision-making can be empowered with an additional layer of data analytics or AI-driven capabilities. This accelerates execution timelines, removes inaccuracies, and provides real-time dynamic support to key departments, thereby improving overall performance. From the time an order is received to processing the order across different stages of the production lifecycle to planning with logistics partners for delivery, automation can eliminate inefficiencies considerably. On the industrial cycle front, workflows can be automated, and controls established through a combination of IoT-enabled equipment, sensors. Etc. bolstered with a dose of intelligent decision-making powered by AI.
Demand forecasting
One of the key drivers of the timely delivery of finished products is the ability to understand and prepare according to demand. But this is not an easy journey, as markets and customer behaviour are dynamic. However, there are underlying patterns or signals that can help manufacturers shed light on the demand pipeline in advance and plan to match them.
This capability is provided by hyper automation, wherein AI and ML-powered systems can dig deep into historical data and identify potential demand signals and spot the same in current market trends. Demand forecasting allows manufacturers to plan their entire value chain and ensure that all stakeholders, including logistics and supply chain, are optimized to support upcoming demand trends. Hyper automation at every step helps in eliminating inefficiencies and adds a layer of visibility into the end-to-end supply fulfillment workflow.
Strengthening quality control
For manufacturers, success in key markets is driven by their competitive strengths, of which higher product quality is a major contributing factor. From the final product produced to the interlayered processes involved in the production cycle, enforcing quality controls across end-to-end workflows is critical for manufacturers. Due to higher manual oversight involved in the quality control workflow, there are often challenges in both the speed of completion of quality checks and missed quality issues due to bias, inefficiencies, mistakes, etc.
Bringing hyper automation into the quality spectrum helps manufacturers to significantly bolster their quality control practices. For processes, intelligent RPA-powered automation bots can validate documents and spec charts for quality checks against benchmarks defined for various activities. As for the product quality assurance, the use of AI combined with visual analytics capabilities will help in discovering even the most subtle deviations in products and help manufacturers pick up defects before they reach the market. AI helps in understanding product design flows accurately and auditing the performance of products against standard conditions to understand deviations, errors, and any misses that may lead to issues in the future.
Seamless asset management
Today’s factories harbour a range of equipment having complex architecture, interweaved with different processes, production, and maintenance cycles. Most manufacturers often struggle to proactively monitor the performance and upkeep of their assets because of the spread and diversity. Preventing breakdowns and disruptions is key to achieving delivery commitments, and manufacturers need to ensure that their hardware assets are in optimal condition throughout the year.
With the rising use of IoT-enabled connected factories, there is enough data available to help streamline asset management. The missing piece is hyper automation that can ensure the free flow of real-time control and operational signals to the right devices without any human intervention needed. Hyper automation ensures that there are rapid responses that occur in the event of an unusual dip in performance. Respective departments will be notified automatically when performance benchmarks slip below a defined threshold. Maintenance cycles are initiated, and repeat audits are done to ascertain the need for a replacement to sustain optimal asset health.
Simplifying the future of industrial workflows
Manufacturing is undoubtedly one of the key drivers of the world economy. Such a crucial sector needs to embrace transformative changes that aid in increasing efficiency, lowering risks, and sustaining profitable growth. One of the biggest steps in that direction is facilitating deep adoption of hyper automation across all layers of the manufacturing cycle. From the use of AI for critical decision-making and IoT for ground-level autonomous operations, the avenues of innovation are countless. The real challenge is making strategic investments in the right technology for the right department at the right time. This is where an experienced technology partner like CSI can make a major difference. From building seamless asset management systems to implementing state-of-the-art industrial automation capabilities with PLC application development services, CSI is equipped to truly understand the digital landscape needed to integrate hyper automation into the core of your manufacturing operations. Over the years, we have enabled some of the world’s best brands to alleviate their manufacturing experience by helping them embrace Industry 4.0 solutions powered by IIOT, AI, and Machine Learning. Our end-to-end services that begin from identifying opportunities to implementation and long-term enhancement and maintenance ensure that manufacturers derive maximum ROI from their investments in hyper automation and their larger digital ambitions.
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FAQ's
Why is hyper automation necessary for manufacturers?
Hyper automation is essential because traditional automation efforts run by rule-based tasks are insufficient to meet the scale of operational complexity demanded by modern manufacturing ecosystems.
What role does AI play in manufacturing?
AI can become a strategic enabler of value across manufacturing industries by helping forecast demands, optimize asset performance, and lower operational costs.
What technologies are involved in hyper automation for manufacturing?
Hyper automation in manufacturing is primarily achieved through a combination of technologies such as AI, IoT, RPA, etc.