Manufacturing Data Analytics: The Next Big Thing

MANUFACTURING
Manufacturing analytics, or real-time manufacturing analytics, is the process of collecting, cleansing, and analyzing data from machines to forecast their future use, prevent failures, forecast maintenance requirements, and identify areas for improvement.

“The goal is to turn the data into information and information into insight.”

- Carly Fiorina, ex CEO of Hewlett-Packard

Manufacturing data incorporates all structured and unstructured information collected manually or through software from machines and humans throughout the manufacturing process, up to the point at which a product is launched to the market.

In this article, we will look at the use cases of data analysis in manufacturing and some of the start-ups from the U.S. that are helping manufacturers gather their real-time manufacturing analytics.


Data Analysis in Manufacturing: Use Case Analytics


Demand Forecasting

Forecasting demand is highly dependent on historical data on supply levels, material costs, purchase trends, and customer behavior. Manufacturers can use analytics to accomplish the following:
  • Define the products to be manufactured in a time frame
  • Define products that are no longer in stock
  • Determine the quantity of products to be manufactured
  • Forecast sales prospects


Inventory Management

Forecasting demand enables manufacturers to manage inventory, purchase materials, and optimize storage capacity based on data. Additionally, manufacturing industry data analysis provides insight into:
  • The sales-to-inventory ratio indicates the average inventory value over net sales.
  • Days in inventory refers to the time a manufacturer retains before selling a product.
  • Gross margin return on inventory (GMROI) is a term that refers to the amount of gross margin a manufacturer receives for each dollar invested in inventory.


Maintenance Optimization

Data collected from various manufacturing machines, tools, and devices, as well as information about operations and the gears required for the machines, can be analyzed to:
  • Predict when a machine will require maintenance based on the amount of time and the operations in which it has been used.
  • Identify and resolve operational anomalies caused by or will result in machine failure.
  • Prevent downtime by scheduling machine breakdowns, repairs, and replacements in advance.


Price Optimization

Utilizing analytics can assist manufacturers in determining the actual cost of a product based on the costs of materials, labor, machines, and tools used or purchased during the manufacturing process. Additionally, manufacturers can optimize prices based on data about competitors, market trends, consumer behavior, and purchase history. Additionally, analytics can assist in setting dynamic prices that are determined by demand, supply, competition, and subsidiary product prices.


Analytics for Manufacturing as a Service: Three U.S.-based Startups


Uptake

Uptake offers predictive analytics solutions powered by artificial intelligence for various industries. It provides a compass, which allows organizations to optimize work orders and scout. This allows users to analyze data and custom alerts and radar to get failure and anomaly detection solutions. Failure prediction, noise filtering, situational analytics, and detecting changes in operational behavior are just a few of the features that these systems offer to their customers today. The product, by Uptake, is intended for use in various industries like mining, construction, fleet management, manufacturing, aviation, government, and oil and gas.


Seeq

Seeq is a leading provider of industrial data analytics solutions. Its big data analysis solutions help in the analysis and comprehension of industrial process data (IPD) more effectively and quickly than typical alternatives. Reduced analysis time, quicker relationship discovery, ERP and other system connectivity, support for business intelligence (BI) tools such as Excel, Tableau, SAS, and MATLAB, and collaboration support are some of the features.


Sight Machine

Sight Machine provides a platform for manufacturing applications that utilize digital twins. It provides solutions for continually analyzing images captured by industrial cameras, sensor data, and data from manufacturing systems to improve product quality and operations. It provides real-time visibility and actionable data for every part, machine, line, and plant manufacturing process. Its clientele includes Nike, Sony, Nissan, and Google, to name a few.


Final Word

Big data analytics in manufacturing assists businesses in identifying the parameters that have a direct effect on production. Additionally, modifying the target process helped businesses increase productivity by 50%.

McKinsey estimates that when analytics are used in design-to-value workflows and projects, manufacturers' gross margins can increase by as much as 40%. Manufacturing analytics can help with design-to-value, supply chain management, and after-sales support. Real-time manufacturing analytics enables manufacturers to optimize their overall production. 


FAQ


Why is data critical in manufacturing?

Big data helps manufacturers understand their customers' needs and wants better. To launch a new product or upgrade an old one, data is required to make it appealing to customers and assess the risks of competition.


What is production analysis?

Production analysis visualizes production output and helps assess production losses and associated costs.


What is predictive manufacturing?

Predictive manufacturing uses descriptive analytics and data visualization to provide a real-time perspective of asset health and reliability performance.

Spotlight

CaptiveAire Systems

CaptiveAire is the nation's leading manufacturer of commercial kitchen ventilation systems. As the industry's innovator, we set the standard for commercial kitchen ventilation equipment and offer the most competitive pricing. CaptiveAire is also known for the fastest and most reliable lead times in the industry.

OTHER ARTICLES
Industrial 4.0

Best Practices for Successful Digital Transformation in Industry 4.0

Article | September 21, 2023

Navigating the path to success by unveiling the best practices for thriving in Industry 4.0 through successful digital transformation. Embrace the data-driven decision-making and customer-centricity. The pursuit of successful digital transformation has evolved from a business strategy to a business necessity. It is a vital imperative for organizations striving to survive and thrive in an ever-competitive market. Within this paradigm shift, a journey unfolds that transcends the commonplace and ventures into the realms of strategic innovation. This best practices article is not just a standard guide but a roadmap to excellence. Explore the best practices that propel businesses into the forefront of Industry 4.0. Beyond the surface of technology adoption lies a deeper narrative, one of cultural transformation, stakeholder collaboration, and visionary leadership. Delve into the intricacies of data-driven decision-making, the agility that fuels progress, the relentless pursuit of knowledge, and the unwavering commitment to the customer experience. Each of these elements forms a crucial thread in the tapestry of successful digital transformation. Through compelling case studies and real-world examples, draw inspiration from industry leaders who have not merely embraced change but have harnessed it to redefine their future. 1. Make confident decisions with Digital Twin Combining the physical and digital realms enables seamless integration of the entire value chain, from design to production, while optimizing with continuous data flow. A digital enterprise can harness the limitless power of data by obtaining valuable insights to make quick and confident decisions and to produce best-in-class products through efficient production. The Digital Twin approach integrates the entire product lifecycle with the factory and plant lifecycles and performance data. The end result is a continuous, open cycle of product and production optimization. The digital twin is a comprehensive digital representation of a product or process throughout its entire lifecycle. By creating a digital twin, companies can achieve significant value, such as faster time-to-market for new products, improved operational efficiency, reduced defects, and exploring new business models to drive revenue growth. With the digital twin, companies solve physical issues more efficiently by detecting them early on and accurately predicting outcomes. It empowers them to design and build superior products and ultimately enhance customer satisfaction by better serving their needs. By adopting smart architecture design, companies can continuously realize iterative value and benefits at an accelerated pace. Manufacturing, automotive, aviation, and other industries have adopted digital twins to boost productivity and efficiency. By 2025, the manufacturing industry is predicted to reach a market size worth over six billion U.S. dollars. 2. Vertically Network Various Units in Enterprise Vertical integration in a Digital Enterprise involves the convergence of IT and OT (Information Technology and Operational Technology) to enable seamless data flow from the shop floor to the top floor. The vast amount of data generated by field devices and control units on the shop floor is vital in the context of Industry 4.0, where intelligent data utilization and communication are paramount. Vertical integration generates a comprehensive solution by integrating IT systems at various hierarchical manufacturing and production levels. These hierarchical levels include the field level (interface with the production process via sensors), the control level (machine and system regulation), the production process level (to be monitored and controlled), the operations level (production planning and quality management), and the enterprise planning level. Vertical integration allows for improved communication and collaboration across different departments within the organization. This leads to better coordination, streamlined operations, and increased efficiency across the entire manufacturing ecosystem. A study by the Boston Consulting Group found that companies with a high level of vertical integration were 16% more productive than those with a low level of vertical integration. 3. Horizontally Integrate the Processes in Lifecycle The concept of horizontal integration in a Digital Enterprise ensures smooth data flow throughout the entire value chain. This integrated approach enables the digitalization of the complete value chain, spanning from design and production to service and recycling. By establishing seamless horizontal integration, it eliminates information silos and creates connections that encompass all aspects, from product innovation and manufacturing to product usage and beyond. Horizontally integrated companies focus on their core strengths and partner to support the value chain. Horizontal integration helps information flow between plant-level Manufacturing Execution Systems (MESs) when a company's manufacturing sites are spread out. This allows production sites to quickly share manufacturing data, such as unexpected delays, breakdowns, and inventory levels. Automated cooperation is crucial to supply chain integration in both the upstream (production processes and downstream (the process of bringing the finished products to market) supply and logistics chains. The integration lets a corporation automatically switch production duties between locations. A study byMcKinseyfound that companies that engaged in horizontal integration in the digital age saw their market share increase by an average of 10%. 4. Upgrade Digitalization using Automation Automation catalyzes growth by streamlining operations, breaking down silos, and promoting cross-functional collaboration. With reduced errors and increased efficiency, businesses can scale their operations with fewer resources, fostering a climate of innovation. This increased productivity allows employees to focus on more creative and challenging tasks, leading to higher motivation and engagement. Furthermore, automation provides a better customer experience, essential in today's digital-savvy market. By automating processes, businesses ensure quick access to customer information, leading to increased satisfaction. Lowering costs and expenditures is another significance enabling businesses to eliminate waste, save time, and conserve resources by automating data entry, approval workflows, and financial procedures. Additionally, automation enables efficient management of decentralized global teams from a central hub, further contributing to cost savings. Automation aids in enhancing security measures and simplifying compliance procedures. Businesses proactively identify vulnerabilities and ensure compliance with ever-changing regulations by automating data-intensive tasks. 97% of IT managers feel process automation is necessary for digital transformation. 5. Implement Additive Manufacturing The adoption of Additive Manufacturing (AM)technologies has prompted the evolution of innovative business models that emphasize environmental perspectives. AM has emerged as a transformative solution within the smart manufacturing industry, offering numerous advantages, such as improved labor, energy, and material optimization, enabling companies to respond to changing market demands effectively. AM is particularly time-saving and cost-effective for small-batch complex geometries products, allowing for non-traditional mass customization and shortening the product development cycle. It encourages changes in sustainable business models, including integrating recycled materials, increasing component attributes, and enhancing product lifecycle. AM’s sustainable benefits have garnered significant attention, focusing on reducing waste, optimizing material consumption, and shortening supply chains. Using layer-by-layer production, AM is considered less wasteful than traditional subtractive methods. It also facilitates the creation of products with extended lifecycles through repair, refurbishment, and remanufacturing, promoting sustainability and environmental responsibility. Study data estimates that the cost savings that can be achieved with Industry 4.0 transformations is 50%. 6. Choose the Appropriate Technology The success of digital transformation endeavors hinges on the careful selection of technologies to invest in. Avoid investing in the latest technology just for the sake of digitization, and refrain from rushing into numerous significant changes simultaneously, which may overwhelm employees. Instead, opt to gradually replace legacy systems and synchronize technology with business objectives through the implementation of new procedures. Here’s what Airbus did. Case Study: Airbus Airbus is the market leader in aeronautics and aerospace products and services worldwide. The organization needed a user-centric digital transformation solution to optimize its data analytics, technology, and machine learning tools, but this proved difficult. Later, it embraced open-source technology and consolidated its 15 tools onto a user-friendly platform. In ten months, this helped produce 290,000 visits and 2,200,000 page views. Additionally, the company's service center is now managing 30% fewer incidents. 7. Adapt Company for a Change Digital transformation does not demand extensive technical expertise from management and employees; rather, it necessitates a shift in mindset. By embracing this new mindset and leveraging technology solutions to automate processes for both customers and employees, rapid growth can be achieved within the organization as well as in the external market. To facilitate this transformation, it is essential to identify areas that require change, enhance transparency, and foster a culture of collaboration within the organization. By taking these steps, an organization can effectively prepare for the changes brought about by digital transformation. Case Study: Honeywell The Fortune 100 manufacturer operates in industries such as aerospace and building technology. To improve product quality and make it easier to apply digital strategies, it cut its operations from eight markets to six. Early in its transformation journey, it established a digital transformation group in the company that led digital innovations like data-driven product offerings, IoT-connected devices, and advanced industrial process control. Honeywell Intelligent Wearables eliminated the need for expert site visits, empowered workers to continue learning, improved their performance, and effectively shared their knowledge with peers by connecting field workers with remote advice. In 2018, Honeywell's share price grew from $95 to $174, and revenue went from $40 billion to $43 billion. 8. 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By prioritizing these practices, businesses can navigate the complexities of digital transformation, drive innovation, and stay competitive in the dynamic landscape of Industry 4.0.

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BizLink, a leading provider of connectivity solutions worldwide, uses a method for creating physical prototypes with computer-aided design (CAD) data. This so called 'Rapid Prototyping' enables development times to be shortened, costs to be lowered and innovative ideas to be realised more quickly. BizLink's Automation & Drives business unit will showcase one of these solutions at the sps trade fair in Nuremberg, Southern Germany, which takes place from 14 to 16 November. In the development and production of individual injection moulded parts, a large part of the cost and time is spent on providing the appropriate tools. That is why BizLink uses Rapid Prototyping for sample parts in the development phase of overmoulded connection components. The principal objective of this technology involves testing and validating design concepts, functionality and features before there is any investment in series production. Through Rapid Prototyping, BizLink thus reduces development costs and time-to-market for overmoulded components and its reinforced innovative cable systems for factory automation. Rapid Prototyping involves applying layer upon layer of materials or bonding them to one another with 3D printing to make the desired object. This makes it possible to quickly adapt the design as changes can easily be made in the CAD data and the prototype can then be reprinted. It also allows, for example, the spatial conditions during fitting and operation under real-life conditions to be assessed, letting the findings thereby acquired be incorporated in product improvement before a tool-maker has even started his or her job. 3D printing technology can furthermore make valuable contributions to quality assurance while development is ongoing. If, for instance, parts being tested must be scrutinised to limit failure mechanisms along functional boundaries, it helps to be able to quickly create a matching testing device for such investigations. In some cases, such devices also facilitate good reproducibility, meaning that dependable component qualifications can also be carried out in this way. Other applications involve trialling numerous production resources and tools as well as handling aids that are, with respect to their function and ergonomics, initially tested as a 3D-printed specimen and improved repeatedly so that they can later be reproduced in a more robust version made of metal, for example. Rapid prototyping is versatile and has long been a proven tool for BizLink in the innovation process to bring new products to market faster and more effectively. Visitors to sps can convince themselves of these advantages through application examples in the Nuremberg exhibition halls from November 14 to 16, 2023 in Hall 2, Stand 431.

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