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Manufacturing Intelligence: How Manufacturing Companies Are Driving Business Transformation
The world has experienced a massive industrial revolution since artificial intelligence stepped into the game. From grocery shopping to manufacturing products, the traditional way of working is almost nowhere. It is not wrong at all to credit 5G technology, IIoT advancements, machine vision, and smart sensing technology for the way product development has evolved from planning and designing to manufacturing and delivering.
Intelligent manufacturing solutions are one such advancement that has affected and assisted manufacturing organizations more than ever before. This intelligent manufacturing technology has taken the place of a majority of traditional industrial rules and enterprises have started implementing manufacturing intelligence in their production firms as this technology assists product development and optimization most effectively.
But how do intelligent manufacturing solutions drive more business growth than traditional manufacturing? This blog will help you understand what manufacturing intelligence is, how to overcome the main challenges of intelligent manufacturing technology, and how it can be leveraged to drive business growth.
Introduction to Manufacturing Intelligence
Intelligent manufacturing is a term that defines the method of optimizing and advancing an industrial manufacturing process to enhance product development and transactions using advanced machine learning techniques. Manufacturing intelligence is a relatively newer industrial development infrastructure that assists with product design, integration, inventory management, and optimization throughout a product’s lifecycle. This technology facilitates data analytics, smart sensors, intelligent devices and materials, and various decision-making models to optimize production quality along with lifelong product service and efficiency.
Intelligent manufacturing also leads to the rise of a well-integrated human-machine industrial manufacturing system. One such example of intelligent manufacturing is the automatic arrangement of parts and materials in product development to facilitate the process. Another example is the optimized controlling and monitoring of a product lifecycle process in real time.
A traditional manufacturing industry can enhance its competitiveness in the market by adapting to intelligent dynamics, and new forms and techniques of intelligent manufacturing to enable smart production.
The use of machine learning algorithms to acquire enterprise manufacturing intelligence allows reasoning, learning, and acting on a decision made with data analytics to optimize production. In today's IIoT era, intelligent manufacturing models allow enterprises to offer personalized, collaborative, flexible, and regenerative services to the end user. But how does this all happen? Let’s understand how this technology contributes to business growth.
How Intelligent Manufacturing Solutions Drive Business Success
Intelligent manufacturing solutions come with benefits that drive massive growth to a business. These rewards include features such as managing and optimizing the industrial system’s efficiency while testing advanced conditions to improve the processes.
Moreover, intelligent process optimization also opens ways to determine the bottlenecks and potential pitfalls in an industrial process. Let's take a look at all those features and perks that manufacturing intelligence can bring to an industry:
Although automation through robotics is already serving manufacturing industries to reduce manpower and speed up processes. But, ever since the integration of machine learning with robotics took place, this hyperautomation has enabled industries to achieve a higher level of intelligent evolution.
Machine learning embedded automation allows manufacturing industries to develop intelligently connected production lines with better performance capabilities and efficiency for its decision-making power.
Intelligent techniques when applied to manufacturing production lines allow the operators to develop advanced algorithms that enable automatic processes. All these advancements in intelligent manufacturing solutions allow manufacturing organizations to skyrocket their business growth.
Warehouse and Supply Chain Management
Intelligent warehouses and supply chain management techniques are other crucial perks that industries leverage from manufacturing-execution-system intelligence to save product handling and maintenance time. The use of cost-effective smart sensors and cloud-native intelligent GPS systems has made it easy for manufacturing industries to perform asset tracking. These techniques provide real-time instant updates on the warehouse inventory and cargo shipments which ultimately assists with better supply chain management and asset transportation.
Industries use this smart technology to develop such intelligent manufacturing solutions that reduce the risk of lost goods in inventory management. Artificial intelligence manufacturing techniques enable the development of efficient responsive systems with capabilities to detect warehouse and supply chain discrepancies. Not just diagnosing the disruptions but also making required adjustments through maintenance systems.
Analytical and Predictive Maintenance
Making required adjustments through predictive maintenance systems is a whole new world in the manufacturing realm. As the IoT and smart sensors periodically monitor the equipment, they mainly track the conditions of equipment and suggest maintenance through analytical reasoning. Hence, this intelligent technology leads to having maintenance scheduled at times only when it is necessary, thus helping organizations save more cost.
Apart from this cost-saving perk, intelligent connected manufacturing solutions allow for minimizing downtime by using analytical reasoning and predicting the equipment's condition. Minimum downtime enables manufacturing industries to target ideal production conditions, hence driving more business growth.
Reduced Time to Market
Intelligent manufacturing leads to faster turnaround times. As the IIoT techniques enable effective communication between the operators and machinery, it leads to better handling and management times. This scheduled management enhances the production speeds and thus enables faster time to market.
The data insights allow the equipment to make analytical decisions through machine learning algorithms, and hence decision-making contributes towards achieving better operational activity and processing. The sooner an industry-built product is finished, the faster it takes to go to market for selling. Hence, through intelligent connected manufacturing, a product takes less time from ideation to production and from production to commercialization which results in a faster time to market.
Focus on Customer Centralization
Last but not least, enterprise manufacturing intelligence allows data analysis of customers’ behavior towards a product, their purchase interests, and preferences. This analysis assists in understanding how a certain product should be developed from the customer's perspective. A customer centered product always results in more sales.
Analyzing customer data to improve products is a form of customer centralization. Know that a customer centralized business always drives more growth and revenue through its work model.
The rise of artificial intelligence in the manufacturing realm has advanced the industry more than ever before. Smart manufacturing is the new norm and businesses are actively implementing this technology to get the most out of it.
Overcoming the Challenges of Smart Manufacturing
Smart manufacturing, when implemented in the right way, has the potential to drive growth more than anticipated. However, it isn’t as easy as it seems due to the challenges that prevail with the risk of derailing the whole investment. Let's have a look at some of the most crucial challenges concerning the implementation of manufacturing intelligence:
Handling Data Sensitivity
One of the most common challenges in intelligent manufacturing is handling data sensitivity. No doubt, data is needed to train and implement an AI algorithm. This data has to be shared across all IIoT devices as well as used in industrial cloud, however, a lot of enterprises are hesitant to share it internally and to third-party handlers due to sensitivity and data theft issues.
One possible solution to such data sensitivity challenges is for organizations to introduce data confidentiality policies for internal enterprise manufacturing intelligence solutions. Moreover, when contracting with third-party developers, adding and highlighting customized policies to ensure safe data handling is mandatory to avoid contract breaches due to sensitivity.
Lack of Training and Technical Skills
As manufacturing industries often include a workforce with more traditional skills, it can become hard for them to fulfill this technical skills gap. The lack of technical skills in the employees can make it very challenging for any organization to drive revenue from their investment.
Connected intelligent experiences demand the implementation and installation of technical digital technology. This makes it necessary for them to have a workforce that possesses strong digital dexterity. The talent must comprehend how the intelligence in the manufacturing processes takes place, thus it demands proper training of technical skills for employees.
Introducing employee learning programs to train them with new concepts and business advancements through change management techniques will allow them to become technically skilled and proficient. When planning on implementing the intelligent model, also research on employee problem assessment as well as problem-solving. The gap can also be fulfilled by hiring external experts and training staff to overcome this challenge and grow as one perceives.
Innovating the Business Model
Innovating the business to integrate manufacturing execution system intelligence is the most challenging task as it involves disturbing the whole business infrastructure and work model. Although it doesn’t have to disrupt the whole organization, still a lot of effort is needed to ensure the right development of enterprise manufacturing intelligence system
For example, H+K International, a leading kitchen equipment manufacturer, was struggling with their legacy ERP based system to manage its inventory. Through legacy system modernization, Icreon helped the company build a web-based enterprise solution for maintaining, updating their product catalogs, and process orders received. With the new intelligent system, H+K is able to gain better business insights into their products and client behavior.
Intelligent manufacturing solutions require special capabilities such as customer and product data analysis of sold products to extract features and embed those features into an intelligent algorithm to enable efficient predictive maintenance. All of this demands an exquisite end-to-end design that needs smooth embedding into the business model. Any enterprise that successfully manages to implement artificial intelligence manufacturing without redesigning the whole business model from scratch wins and benefits from the perks listed above. Hiring an innovation consultant to innovate your business model can assist in overcoming this challenge.
Lack of Interoperability
The inability to innovate, called interoperability, is another challenge that prevails when building smart connected intelligent experiences. Enterprises often find it hard to swap out one system to innovate the other and upgrade one component to support the other, hence the flexibility to innovate becomes very limited.
This situation becomes easier to handle if the vendors develop such intelligent solutions that support universality throughout a production firm. Moreover, using standardized development through open-source options also assists in overcoming the lack of interoperability.
Master Digitization to Manufacturing Intelligence
The digitization process in any organization needs such an ecosystem that supports smart business processes, intelligent transactions, and innovation capabilities. The same is the case for implementing connected manufacturing experiences through artificial intelligence.
Any manufacturing organization that still supports traditional industry practices is often left behind in the competition and then finds it hard to innovate when the need arises. Lately, there have been tremendous advancements in the manufacturing realm that infuse artificial intelligence technology resulting in smart connected solutions.
If you are among such traditional industries, now is the time to innovate and implement smart solutions. At Icreon, we provide stellar services to help businesses innovate with the latest industry standards. Explore our Digital Transformation Services to start winning in the IIoT-based smart manufacturing competition.