To streamline processes, several industries are undergoing digital transformation. The manufacturing sector, on the other hand, has been slow. However, the time has come to use data analytics in manufacturing to ensure better decision-making and performance.
Industry 4.0, when combined with the rapid development of artificial intelligence, advanced analytics, robotics, and emerging IoT-powered sensors and devices, allows manufacturers to collect, store, process, and use data in their daily operations. Additionally, business intelligence and business analytics aid in the discovery of potential improvements.
Furthermore, new solutions to automate large-scale processes and reduce execution time are frequently required in the manufacturing industry. We hope to demonstrate how data analytics can transform the manufacturing industry in this blog post.
Get ready with the industry 4.0 revolution
Industry 4.0 is not a simple concept; it encompasses a wide range of technologies for a variety of applications. Manufacturers who use Industry 4.0 digital solutions, on the other hand, are better positioned to move faster than traditional businesses. With the power of connectivity, advanced analytics, automation, and more, everything from production efficiency to product customization can be transformed. Manufacturers can improve speed to market, improve service effectiveness, and create a new business model for increased productivity by combining these technologies.
Industry 4.0 is the way to go if an organisation wants to improve the resilience of their supply chain, restore operations, or overcome production challenges.
For a better understanding, here’s a diagram that shows the foundational technologies of Industry 4.0:
Let’s understand some data challenges in manufacturing:
- For manufacturers, the increasingly distributed data, which is frequently collected from multiple sources and presented in inconsistent ways, poses a challenge. Although many organisations can correctly capture data, they fail to analyse and utilise it effectively.
- Integration of new technologies into legacy systems such as ERPs, machine-level control systems, execution systems, and even production planning systems is another data challenge.
- Not to mention, the rapid generation and collection of industrial data by manufacturers necessitates the overhaul of storage management systems, which further fails to keep up with timeliness.
- The visualisation and interaction tools become more complex as the volume and complexity of data grows. Manufacturers should be aware of the impact of this data challenge, even if they are not in charge of solving it.
- The use of multiple connected tools and industrial control systems can cause gateways connecting various IoT devices to become overloaded. Furthermore, manufacturers may be vulnerable to unauthorised access, leaks, and security issues due to limited computing power.
Now that we’ve gone over some of the data challenges, let’s look at how data analytics in manufacturing can help us solve these problems.
How is the manufacturing sector innovating with data analytics
Analytics provides actionable insights that explicitly support a company’s most critical business decisions, such as locating:
- How is the manufacturing industry using data analytics to innovate?
- Which vendors are most likely to cause a disruption in our manufacturing process?
- What is your company’s competitiveness in terms of sales incentives?
Because products are usually at the centre of the manufacturing process, the first wave of analytics focuses on improving product growth. Supply chain optimization, sales and marketing budget control, warranty spending reduction, and overall financial management improvements are all common areas of focus.
In these fields, data analytics can provide breakthrough insights that have a significant impact on business results, as well as an incredible return on an organization’s analytics investment. Furthermore, the use of analytics can promote new revenue models based on selling a manufacturing company’s services.
Here are few ways how data analytics can help manufactures
1. Keeping operational costs low
What if employees could conduct a supply chain analysis right away? What if a collaborative, enterprise-wide sales dashboard could aid in the tracking of revenue? Manufacturing employees can handle ad hoc queries in seconds thanks to search-driven data analytics. They are embedded in shared workflows and portals and receive results in the form of a visualisation model with easy-to-read data.
This will assist in determining how a manufacturing unit spends funds, as well as eliminating costly reports or data solution pay-per-user licence fees.
2. Human labour and automation balancing
Many manufacturers struggle to keep warehouses in good order and automate certain processes. Humans, on the other hand, are indispensable in certain roles, such as supervisors. Manufacturers can introduce workable staffing solutions and track ROI over time by leveraging workforce analytics, especially as they adopt automation in various segments of their operations.
3. Cyber-threats and data breaches
When it comes to cyberattacks, a variety of best practises are involved, including phishing scam prevention, employee training, antivirus updates, and more. These are critical considerations for manufacturers, especially when large amounts of data are collected frequently. As a result, implementing an enterprise-grade data security solution aids in the protection of data from misuse. Here are a few benefits to consider:
- Permissions for specific authorizations
- Every data object, level, and row has a security layer.
- Data governance and management on a single platform
- Data insights that are auditable and traceable
4. Decision-making that is effective
Analytics in manufacturing not only aids in effective decision-making, but it also aids in the resolution of operational issues. Manufacturers can examine billions of data rows from various sources using data analytics, allowing them to identify inefficiencies, opportunities for organisational improvement, and share insights with authorised users.
Manufacturers: Data is the key to success.
Data-driven manufacturing, which unifies both internal and external data, is becoming a strategic necessity. Manufacturing companies should use data analytics to extract significant value faster and more efficiently as data grows exponentially. Get in touch with our experts and begin your data journey if you’re ready to make a significant impact with data.