With Industry 4.0 and the Industrial Internet of Things (IoT), a digital transformation is currently underway. The construction industry is using analytics powered by real-time production data, to enable not only better, faster decision-making, but automation across the organization.
COVID-19 has severely affected the manufacturing industry, and in the second and third quarters of 2020, global manufacturing output declined by 11.1% and 1.1% year-on-year.

Manufacturing analytics is the use of data and technologies from operations and events in the construction industry to ensure quality, increase performance, reduce costs, and optimize supply chains. Manufacturing analytics are part of a wider revolution known as Industry 4.0, where factories are expected to grow into self-run and healing entities by adopting new technologies such as the cloud and Internet of Things (IoT).

Applying Bizintel360 Manufacturing Analytics in Business

product development

Product development is an expensive process in manufacturing. To remain competitive, companies must pay for R&D to create new product lines, improve existing models, and develop new value-added services.
Previously, this was done through highly iterative modeling to arrive at the best product. But now, data science and advanced manufacturing analytics make it possible to simulate much of this process. Using “digital twins” and other modeling methods, real-world situations can be generated virtually to predict performance and reduce R&D costs.

price optimization

Cycle times play a major role in pricing. And knowing the exact timing for partial manufacturing and associated costs allows for accurate cost models and customized pricing strategies. Setting them too low reduces profitability while setting them too high can affect demand. An advanced analytics platform for manufacturing can bring this data forward to ensure that prices are set appropriately. Machine metrics can help manufacturers optimize their job standards to ensure accurate cycle times.

managing supply chain risk

Like data coming in from production machines, data can also be captured from materials in transit and transmitted directly from vendor equipment to software platforms to help provide end-to-end visibility into the supply chain.
They can also order backup supplies and buffer stock when new demand is sensed and trigger secondary sellers when disruptions occur.

Demand Forecasting and Inventory Management

Forecasting demand is important for modern manufacturers and having complete control over the supply chain allows for better inventory control.
But demand planning can be complicated. With the addition of data science methods, end-to-end control of the supply chain can be used with real-time shop floor data to better manage purchases, inventory control, and transportation. Highly accurate demand plans can be drawn that identify trends that would otherwise go unnoticed.
With a better understanding of how long it takes to make parts, how long the job will take, and the expected cost and benefits of a job, manufacturers can better estimate their need for materials to plan improvements.

Benefits of Using Bizintel360 Manufacturing Analytics

Automate human processes
Besides improving production, companies are also using analytics to revolutionize back-end processes. Robotic Process Automation (RPA) combines analytics, Machine learning and rule-based software to capture and interpret the existing data-input stream to be processed a transaction, manipulating data, triggering responses and communicate with other enterprise applications.

Improve operations for more revenue

Operational efficiency in manufacturing is based On customizing all aspects of the production line, As well as inbound and outbound supply chain. Analytics is an important tool to reduce downtime, production scheduling and demand forecasting commensurate with capacity and logistics constraints. before they break or prevent incidents, occurrence is an important step in risk management and This is the key to making sure your plant is operating at maximum capacity. Logistics, total visibility in inventory and dealer networks can also help eliminate End-to-end production lifecycle bottlenecks.

Improve new product development

Creating an innovative product is an expensive and risky proposition. Analytics can remove most of the guesswork involved in designing a product to help ensure you are providing the features and level of quality your customers expect.

Less cost

Because processes can be optimized with the insights revealed in analytics, costs can be significantly reduced. And with the development of robotics, autonomous or semi-autonomous machine decision-making reduces labor. The same is true of predictive and prescriptive maintenance programs proven to reduce costs and increase productivity by reducing downtime and better managing parts inventory.

increased revenue

With real-time insights into production, inventory management and demand and supply planning, manufacturers can respond quickly to changes in demand. Let’s say the data tells them they are close to maximum capacity. In that case, they may add additional time, add capacity, alter processes, or adjust other aspects of production to respond to and maintain delivery times.

About Bizintel360 Advanced Analytics

BizIntel360, a truly self-service big data analytics solution that combines the advantages of the cloud with the advanced capabilities of today’s data warehousing and visualization solutions.
With Bizintel360, analyze and visualize data to discover actionable insights for decision making. Get predictive analytics with real time data. Find patterns, trends, churns and many more metrics to empower your business.