Article | December 14, 2021
The manufacturing industry has evolved to new heights of innovation, productivity, and excellence with digital transformation. Manufacturing digitalization has made operational procedures more skilled, accurate, and time-savvy.
“Many companies simply are not willing to change or think they are done once they make a change. But the truth is technology; consumer demands, the way we work, human needs and much more are constantly changing.”
Michael Walton, Director, Industry Executive (Manufacturing) at Microsoft
With a CAGR of 19.48 percent between 2021 and 2026, the digital transformation in the manufacturing market is expected to reach USD 263.93 billion by 2026. Manufacturing plants adopt digital technology to improve, automate, and modernize processes as part of Industry 4.0.
So, what are the key benefits of digitalization for manufacturers? This article will elaborate on the top five benefits of digital manufacturing transformation.
How to Define Digital Manufacturing?
Manufacturing digital transformation involves integrating digital technologies into processes and products to improve manufacturing efficiency and quality. Manufacturing's digital transformation aims to increase operational efficiency and reduce expenses. The digital transformation techniques ensure product quality. It also makes work more efficient, safe, and stress-free.
What Is Included in Manufacturing Digitization (Industry 4.0)?
Industry 4.0 is the digitalization of manufacturing. Cyber-physical systems, IoT, and cloud computing are current trends in manufacturing automation and data exchange. Connected devices, cloud computing power, and the modern emphasis of lean, efficient operations enable Industry 4.0 to construct advanced and innovative smart factories.
Industry 4.0 includes design, sales, inventories, scheduling, quality, engineering, customer and field service.
Five Benefits of Digital Transformation in Manufacturing
Manufacturing organizations can benefit from digitalization in a variety of ways. It can help make the work more efficient, decentralized, and secure. It further creates new business opportunities and attracts new talent to the industry. Additionally, integrating products into a digital ecosystem increases their value and appeal. Let’s dig deeper into each of the five key benefits.
Technology is an invaluable companion in reducing the manufacturing company's expenses in the future. The incorporation of digital technology results in the transformation of procedures and the digitization of documents, resulting in overall process optimization. Therefore, a reduction in labor costs might be expected as a result of the elimination of unnecessary expenditures.
Additionally, digitization enables businesses to assess and estimate expenses considerably more precisely, ensuring that budgets stay on track. Additionally, it eliminates andsubstitutes inefficient jobs within processes, significantly increasing their efficiency. This efficiency is translated into time savings, which results in a substantially more cost-effective manufacturing process.
Manufacturing digital transformation allows organizations to supervise manufacturing remotely, allowing production to continue uninterrupted. In rare cases like Covid-19, digitalized businesses have not had to cease or even slow down production. These systems can work without interruptions for much longer than any worker.
Digitalization also boosts methodology flexibility and reactivity. For example, if a production plant has a problem, an automatic alert is generated, and the issue is resolved regardless of the day, time, or presence.
Improved Operational Efficiency
Smart product connectivity allows devices to connect and communicate with each other (M2M). This connectivity enables decentralized decision-making. Many duties no longer require an employee to be physically present. New manufacturing and production models minimize boring, risky activities while increasing accuracy, efficiency, and responsiveness.
Transforming businesses through digital means making better decisions based on real-time data. Training, changes, and repairs are no longer issues due to reduced frequency and automation.
New Business Opportunities
New digital technologies enable the manufacture of previously unviable products and services, generating new revenue streams. Also, new services (innovation or reorientation) are launched considerably faster. Companies may utilize big data and AI to experiment, anticipate trends, and predict about new advancements. These technologies can help organizations become more eco-friendly and create products that are less detrimental to our environment.
Attracts New Talent
Professionals with fundamental talents in this complicated and disruptive environment are drawn to digitalizedorganizations that are up-to-date with trends and processes. Also, if the change is managed well, it will lead to higher profitability, increasing employee satisfaction. Human motivation, along with excellent digital technologies, will reflect in the company's production and profitability.
Dusseldorf@Germany: The Deloitte Digital Factory
The digital factory in Dusseldorf provides a flexible setting for innovative workshops and training, bringing together the old and new worlds of supply chain and industrial operations to provide a seamless experience. Specific use case examples, as well as the digital solutions sector, will motivate and encourage businesses to get on their digital transformation journeys, making use of the most up-to-date technologies in the process.
Manufacturing digitalization has a lot to offer the industry, and many manufacturers are capitalizing on this new phase of the industrial revolution by incorporating cutting-edge technologies into manufacturing and business operations. As said previously, the benefits of digital transformation in the manufacturing business are increasing the importance of digitalization in the industry. Transform your traditional manufacturing operating processes with these new manufacturing trends and observe the results that other benefitting manufacturing businesses have achieved.
Why is digitalization vital in manufacturing?
Manufacturing process digitization improves overall business performance. But the results are seen across the factory. Digital transformation improves working conditions for employees and streamlines daily operations.
How are digitization and digitalization different?
Digitalization is a transformation of data and processes. Digitalization is the use of digital technologies to collect data, identify patterns, and make better business decisions.
How digital technologies are applied in manufacturing?
Digital manufacturing technologies enable the integration of systems and processes across all stages of production, from design to production and beyond.
Article | December 8, 2021
The new manufacturing industry outlook for 2022 is what businesses desire. Due to COVID-19, the sector has seen several ups and downs in recent years. But the industry overcame the most difficult situation by adopting innovations as their working hands.
But all this upgrading and digitalization in manufacturing isn't for everyone. Some manufacturers may struggle with this change, while others may not. So, taking into account all industry segments, we have compiled a list of potential manufacturing challenges for 2022.
“Many companies simply are not willing to change or think they are done once they make a change. But the truth is that technology, consumer demands; the way we work, human needs and much more are constantly changing.”
– Michael Walton, Director, Industry Executive (Manufacturing) at Microsoft
The summary of manufacturing industry challenges and industry outlook for 2022 are presented in the stats below.
According to the National Association of Manufacturers (NAM), four million manufacturing jobs will likely be needed over the next decade, and 2.1 million will likely go unfulfilled unless we motivate more people to pursue modern manufacturing occupations.
According to PTC, 70% of companies have or are working on a digital transformation plan.
According to Adobe, 60% of marketers feel technology has increased competitiveness.
The statistics show that while digitalization facilitates the process, it also poses several challenges that must be addressed in the coming years. Let's explore what obstacles manufacturers may face in 2022.
The Manufacturing Industry Challenges in 2022
The manufacturing business has had a difficult few years as a result of the current economic downturn, and 2022 may not be even that smooth. Thought, technology, and current trends make the operations of upscale manufacturers easier, but not everyone is on the same page.
Let's look at some of the manufacturing challenges that businesses will face in the next year.
Skilled Labor Shortage
The manufacturing industry is facing a workforce shortfall as a skilled generation prepares to retire. Industry experts say that by 2025, there will be between 2 and 3.5 million unfilled manufacturing jobs. As a result of the advancement of new technologies, manufacturing organisations are finding themselves with fewer personnel. They do, however, require individuals with a diverse range of abilities, such as mathematicians and analytic thinkers, to accomplish the tasks with precision.
Specific manufacturing tasks have been automated to save time and money. Industry has adopted machine sensors to capture large amounts of data. With this kind of innovation, the industry's job structure is changing and the desire to hire an untrained or trainable workforce is slowly fading in the industry. However, using augmented reality and virtual reality, manufacturers can easily train personnel for the job and save money.
Lack of Ability to Mine Data
Manufacturing is progressively using IoT. The majority of businesses have already installed or are planning to install Internet of Things machines. These smart machines let businesses collect data to improve production and conduct predictive maintenance. But getting data is a simple task. The difficult aspect is analyzing and aggregating data.
Despite possessing the machines, most companies lack the systems to analyze and retrieve the data recorded by the systems. In this way, the industries are missing a vital opportunity. The industry must improve data mining capabilities to make better decisions in real-time.
Using IoT for analytics and predictive maintenance is critical. Monitoring technologies can help the sector examine data quickly. It can also help predict an asset's maintenance period. As a result, the industry will move from replacement to predict and fix.
Self-service Web Portals That Is Extremely Detailed and Precise
Manufacturing businesses usually strive for on-time order delivery and optimum revenue. However, consumer self-service, which has been in the industry for a long time, has never proven to be a simple walk for clients. Clients are frequently required to pick up the phone and contact manufacturers in order to track their orders and receive delivery estimates. This is hardly the service one would expect from a manufacturer, even more so in today's digital era.
The term customers in manufacturing include partners, end-users, and subcontractors. These three clients have distinct requirements and concerns about collaborating with the manufacturer. Companies can better serve their customers if their partner and end-customer portals are linked to a central hub which we can mention as self-service web portals.
All of the information and updates they need about their orders will be available to them through this new system. They can track, accept and amend their tasks. They'll also use the self–service portal to contact the manufacturer.
In this way, manufacturers can better serve their customers. A system like this will ensure that all parties have access to timely information in a digital format.
Meeting the Deadline for the Project
Product launch timelines are extremely demanding, tight, and stringent. Every project in the assembly line is about cost, time, and quality. Ultimately, these projects are rigorous and well-controlled. Manufacturers who fail to meet deadlines risk losing millions in potential revenues and sales.
Due to rigidity and stringent control, companies are less able to change project scopes or make adjustments as projects develop. The majority of initiatives begin with a design commitment. As new facts or change criteria emerge, adjustment flexibility decreases. This can be aggravating for a team that expects high-quality results. Deadlines are always a constraint.
Effective Business Digital Marketing Strategy
An industry's key digital transformation challenges are driving leads, sales, and MRR through digital channels. Many manufacturing organizations struggle to efficiently use marketing channels like paid media, enterprise SEO, local SEO, content strategy, and social media. In our opinion, one of the most significant issues these organizations have is their digital experience, website design, and overall brand presentation. They can't ignore them if they want to keep enjoying the manufacturing revival.
Visibility of the Supply Chain
Manufacturers must respond to the growing demand from customers for greater transparency. In order to meet customer demand across the customer experience and product lifecycle, they must first understand that precise and real-time visibility throughout the supply chain is essential.
All details must be taken into consideration by the manufacturers. They must be aware of any delays in the arrival of products on the market. Keeping abreast of such developments would give them a leg up in terms of adjusting or rectifying the situation.
Manufacturing industry challenges have long been a part of the industry. However, industry leaders and professionals have always confronted and overcome any challenges that have come their way. The year 2022 will also be a year of achievements, setting new records, and growth for the manufacturing industry, since it will be a year in which it will develop solutions to all of the aforementioned challenges.
What is the future of manufacturing?
Manufacturers should start using AI, block chains, and robotics today. The combination of these new technologies will reshape manufacturing. A new workforce capable of augmenting these technologies is developing and will become the future of manufacturing.
How will automation affect manufacturing in 2022?
When applied properly, automation can greatly assist manufacturing. These benefits include shorter production times, faster and more efficient work than human labor, and lower production costs.
How is the manufacturing industry’s market likely to upsurge in the future?
According to BCC Research, the global manufacturing and process control market is expected to grow at a CAGR of 6.3 percent from $86.7 billion in 2020 to $117.7 billion in 2025.
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"text": "Manufacturers should start using AI, block chains, and robotics today. The combination of these new technologies will reshape manufacturing. A new workforce capable of augmenting these technologies is developing and will become the future of manufacturing."
"name": "How will automation affect manufacturing in 2022?",
"text": "When applied properly, automation can greatly assist manufacturing. These benefits include shorter production times, faster and more efficient work than human labor, and lower production costs."
"name": "How is the manufacturing industry’s market likely to upsurge in the future?",
"text": "According to BCC Research, the global manufacturing and process control market is expected to grow at a CAGR of 6.3 percent from $86.7 billion in 2020 to $117.7 billion in 2025."
Article | December 21, 2021
Consumer demand has shifted dramatically in recent years, and manufacturers are trying to adapt to this shift. To maintain high product quality, minimize costs, and optimize supply chains, manufacturing analyticshas become essential for manufacturers.
Manufacturing analyticsis the process of gathering and analyzing data from various systems, equipment, and IoT devices in real-time to get essential insights.
As technology takes over and enhances many of the processes we used to handle with manual labor, we are freed up to use our minds creatively, which leads to bigger and better leaps in innovation and productivity.
– Matt Mong
Manufacturing analyticscan assist in maintaining production quality, boost performance with high-profit returns, decrease costs, and optimize supply networks.
This article will outline manufacturing analyticsand present a list of possible application cases. It will also highlight the benefits of manufacturing analyticsfor any shop floor or factory.
Manufacturing analytics: An Overview
With manufacturing analytics, we can streamline and speed up the entire process. Data interchange and automation helps in speeding up the production process. Manufacturing analyticsuses predictive manufacturing, big data, Industrial IoT, network virtualization, and machine learningto produce better scalable production solutions.
Manufacturing analyticscollects and analyses data from many sources via sensors embedded in machinery to identify areas for improvement. Data is collected and presented in an easy-to-understand structure to illustrate where difficulties emerge throughout the process.
In short, manufacturing analyticscollects and analyses large volumes of data to reveal insights that might improve performance. Users can also obtain automated business reports to reply in real-time.
Why Manufacturing analytics is Vital for Leading Businesses
There are numerous benefits of manufacturing analyticsthat drive any company’s production and overall manufacturing business growth. The benefits of manufacturing analyticsfall into three distinct categories as below.
It reduces the overall cost: Analytics may save a significant amount of money if used more efficiently. Labor costs are also reduced due to automation and semi-autonomous machinery. Similarly, preventive and prescriptive maintenance programs may save money while enhancing productivity.
It boosts profits for businesses: Manufacturers can respond swiftly to changes in demand using real-time insights in production, inventory management, and demand and supply forecasting. For example, assume the data indicates that they are approaching their maximum capacity. In such instances, they can increase over time, increase capacity, modify procedures, or tweak other production areas to adapt and maintain delivery times.
Other unforeseen benefits: There are several advantages to the increased capabilities enabled by manufacturing analytics. These benefits include lower energy use, safer environmental practices, fewer compliance failures, and more customer satisfaction.
Five Real-world Applications of Manufacturing Analytics
A machine's analytics uses aggregate data from real-time detectors to anticipate when it needs to be replaced or functioning irregularly. This process helps predict machine failure or equipment defects.
Analytics can assist in determining a plant's capacity and how many products are produced by the unit in every production cycle, which is helpful in capacity planning. In addition, analytics may help determine the ideal number of units to create over time by considering capacity, sales predictions, and parallel schedules.
Predictive analytics solutions can automate maintenance requests and readings that shortens the procedure and reduce maintenance expenses.
Product development is an expensive process in manufacturing. As a result, businesses must invest in R&D to develop new product lines, improve existing models, and generate new value-added services.
Earlier, this approach was in place by repeated modeling to get the finest outcome. This approach can now be modeled to a large extent, with the help of data science and technologically superior analytics. Real-world circumstances can be replicated electronically using "digital twins" and other modeling approaches to anticipate performance and decrease R&D expenses.
Many factors that might help in the plan significant capital expenditures or brief breakdowns can be explained using historical data and a few high-impact variable strategies. For example, consider the seasonality of products like ice cream. As a result, historical market data and a few high-impact factors can help explain numerous variables and plan major capital expenditures or short-term shutdowns.
In addition to demand forecasting, predictive analytics incorporates advanced statistical techniques. With predictive analytics, a wide range of parameters, including customer buying behavior, raw material availability, and trade war implications, may be taken into consideration.
Warranty support may be a load for many manufacturers. Warranties are frequently based on a "one-size-fits-all" approach that is broader. This approach introduces uncertainty and unanticipated complications into the equation.
Products may be modified or updated to decrease failure and hence expense by using data science and obtaining information from active warranties in the field. It can also lead to better-informed iterations for new product lines to minimize field complaints.
Managing Supply Chain Risks
Data may be recorded from commodities in transit and sent straight from vendor equipment to the software platform, helping to enable end-to-end visibility in the supply chain.
Manufacturing analyticsallows organizations to manage their supply chains like a "control tower," directing resources to speed up or slow down. They may also order backup supplies and activate secondary suppliers when demand changes.
Businesses should adapt to changing times. Using analytics in manufacturinghas altered the business industry and spared it from possible hazards while boosting production lines. Industry 4.0's route has been carved. Manufacturing analyticsis the key to true Industry 4.0, and without it, the data produced by clever IoT devices is meaningless. The future is data-driven, and success will go to those who are ready to adopt it. The faster adoption, the sooner firms go ahead of the competition.
How can data analytics help manufacturers?
Data analytics tools can help manufacturers analyze machine conditions and efficiency in real-time. It enables manufacturers to do predictive maintenance, something they were previously unable to accomplish.
Why is data so crucial in manufacturing?
Data helps enhance manufacturing quality control. Manufacturers can better understand their company's performance and make changes by collecting data. Data-driven manufacturing helps management to track production and labor time, improve maintenance and quality, and reduce business and safety concerns.
What is Predictive Manufacturing?
Predictive manufacturing uses descriptive analytics and data visualization to offer a real-time perspective of asset health and dependability performance. In addition, it helps factories spot quality issues and takes remedial action quicker by eliminating the waste and the cost associated with it.
Article | December 8, 2021
A digital twin is a virtual model of an object or system that comprises its lifecycle. It is updated with real-time data and aids decision-making through simulation, machine learning, and reasoning for the production system.
IoT sensor data from the original object is used to create a digital twin of the system. This cloud-connected data allows engineers to monitor systems and model system dynamics in real-time.
Modifications can be tested on the digital twin before making changes to the original system.
Considering that digital twins are supposed to replicate a product's complete lifecycle and are used throughout the production process, it's not unexpected that digital twins have become prevalent in all stages of manufacturing.
“More than a blueprint or schematic, a digital twin combines a real-time simulation of system dynamics with a set of executive controls,”
– Dr. Daniel Araya, consultant and advisor with a special interest in artificial intelligence, technology policy, and governance
Companies will increasingly embrace digital twins to boost productivity and decrease expenses. As per recent research by Research and Markets, nearly 36% of executives across industries recognize the benefits of digital twinning, with half planning to implement it by 2028.So how does this digital twin technology benefit modern manufacturing? Let's have a look.
How the Digital Twin Drives Smart Manufacturing
Digital twins in manufacturing are used to replicate production systems. Manufacturers can develop virtual representations of real-world products, equipment, processes, or systems using data from sensors connected to machines, tools, and other devices.
In manufacturing, such simulations assist in monitoring and adapting equipment performance in real-time. With machine learning techniques, digital twins can predict future events and anticipate potential difficulties.
For maintenance, digital twins allow for quick detection of any problems. They collect real-time system data, prior failure data, and relevant maintenance data. The technique employs machine learning and artificial intelligence to predict maintenance requirements. Using this data, companies can avoid production downtime.
Digital Twin and Artificial Intelligence (AI) in manufacturing
Using digital twins and AI in production can enhance uptime by predicting potential failures and keeping equipment working smoothly. In addition, there are significant cost savings in the planning and design process as digital twins and AI can be used to replicate a specific scenario.
Maintenance is another area that has seen significant progress with the use of digital twin manufacturing. A Digital Twin powered by AI can predict when a piece of equipment will fail, allowing you to arrange predictive maintenance that is not simply taking information from OEM manuals but can significantly cut maintenance expenses along with reducing downtime.
Using the digital twin, it is feasible to train virtual workers in high-risk functions, similar to how pilots are trained using flight simulators. It also frees up highly skilled workers to upgrade the plant and streamline operations.
General Electric Created the Most Advanced Digital Twin
General Electric Company (GE) is a multinational business based in Boston that was founded in 1892. It has developed the world's most advanced digital twin, which blends analytic models for power plant components that monitor asset health, wear, and performance with KPIs (Key Performance Indicators) determined by the customer and the organization's objectives. The Digital Twin is powered by PredixTM, an industrial platform built to manage huge amounts of data and run analytic algorithms. General Electric Company provides extra "control knobs" or "dimensionality" that can be utilized to improve the operation of the system or asset modeled with GE Digital Twin.
Given the numerous advantages of digital twin manufacturing, the potential for digital twins to be used in manufacturing is virtually endless in the near future. There will be a slew of new advancements in the field of digital twin manufacturing. As a result, digital twins are continually acquiring new skills and capabilities. The ultimate goal of all of these enhancements is to create the insights necessary to improve products and streamline processes in the future.
What is a digital twin in manufacturing?
The digital twins could be used to monitor and enhance a production line or perhaps the whole manufacturing process, from product design to production.
How digital twin benefit manufacturers?
Using digital twins to represent products and manufacturing processes, manufacturers can save assembly, installation, and validation time and costs.
What is a digital thread?
A digital twin is a realistic version of a product or system that replicates a company's equipment, controls, workflows, and systems. The digital thread, on the other hand, records a product's life cycle from creation to dissolution.
"name": "What is a digital twin in manufacturing?",
"text": "The digital twins could be used to monitor and enhance a production line or perhaps the whole manufacturing process, from product design to production."
"name": "How digital twin benefit manufacturers?",
"text": "Using digital twins to represent products and manufacturing processes, manufacturers can save assembly, installation, and validation time and costs."
"name": "What is a digital thread?",
"text": "A digital twin is a realistic version of a product or system that replicates a company's equipment, controls, workflows, and systems. The digital thread, on the other hand, records a product's life cycle from creation to dissolution."