The State of Data Towards Digital Transformation in the Manufacturing Industry
Journey to Industry 4.0 Series — with Cloudera
Andi Sama — CIO, Sinergi Wahana Gemilang with Cahyati S. Sangaji, Nurholis Seha, Andrew Widjaja, and Tommy Manik
A recent 2023 survey (Endeavour Business Intelligence, 2023), conducted by Smart Industry in partnership with Cloudera sought to understand how manufacturers plan to gain insights from their data and the challenges they face or expect to encounter along the journey toward Industry 4.0.
Among other things, the survey data, acquired from 110+ respondents, seeks to determine which area of investment focus that are key to achieving the following business outcomes:
- Reducing operational costs.
- Improving the customer experience.
- Improving product quality.
- Gaining a competitive edge.
76% of respondents come from manufacturers with annual revenue over USD 1B, considered enterprises; the rest are SME — Small Medium Enterprises with employees over 500 and annual revenue between USD 50M — 1B. 91% of respondents are located in the United States of America. Respondents are distributed in Europe, South America, the Middle East, Africa, and Asia.
Participating industries include transportation and industrial equipment, advanced electronics and semiconductors, automotive and assembly, aerospace and defence, oil and gas, metals, chemicals, food and beverage, consumer goods, basic materials, medical devices, and pharmaceuticals.
The findings concluded that less than 50% of the respondents are collecting sensor/IoT (Internet of Things) data or application and security logs today, and only about one-third are utilizing streaming or real-time data. This could indicate that legacy technology is preventing manufacturers from fully unleashing the value of data.
The use of data & analytics in manufacturing organizations is mainly to solve problems around product quality, process automation, asset maintenance, and demand forecasting or inventory management.
The need for a robust and scalable data platform is obvious to manage better and extract insights from the data. Some challenges are:
- Legacy infrastructure and systems that cannot support the volume of data.
- Silos of data across different organizations and business units.
- The complexity of the data environment.
The legacy infrastructure and systems include manufacturing operational data, the OT — Operational technology side (Andi Sama, Cahyati S. Sangaji, 2023) coming from sensors, actuators and controllers across multiple production lines and sites (PLC — Programmable Logic Controller, HMI — Human Machine Interface, SCADA — Supervisory Control and Data Acquisition, DCS — Distributed Control System, MES — Manufacturing Execution System, ERP — Enterprise Resource Planning, and DSS — Decision Support System, for example).
Many manufacturers (48%) are trying to overcome these challenges through hybrid or multiple cloud approaches for improved data management. Those are driven by the need to streamline business operations applications, reduce costs, and improve security and governance.
- 64% of the hybrid/multi-cloud adopters agree that the approach has helped them achieve their business goals. Towards the future, most manufacturers (68%) expect to increase the amount of data managed in the cloud over the next 12 months, whether hybrid, private, or multiple cloud providers.
- 56% of respondents see value in moving all data to a hybrid cloud.
- On the other hand, 41% agreed that some data must remain on-premises or in a private cloud. A good reason to rely on a management platform that helps unify data across all these environments is to analyze it better and gain insights.
Enabling Intelligence in Manufacturing
The rapid advancements in IT — Information Technology like IoT, Bigdata, Machine Learning and Artificial Intelligence open up the opportunity for advanced analytics for OT data. The concept of Industrial IoT (IIoT), leveraging IT to process OT data, has been increasingly adopted by manufacturers, hence the term IT/OT convergence towards Industry 4.0.
The manufacturing industry is no exception; the opportunity to apply advanced analytics on operational data coming from various sensors, actuators, and controllers lays the foundation for intelligence manufacturing, such as predictive asset maintenance instead of scheduled maintenance, contributing to better product quality and process automation.
Edge analytics is possible by analyzing real-time operational data through IIoT, by acquiring sensor data to detect anomalies of the running 3-phase AC motor through vibration pattern, for example, advising maintenance personnel for a better schedule to perform maintenance ahead of a potential machine breakdown, rather than just doing scheduled or ad-hoc maintenance of the high-value production assets.
Cloudera as the Platform to enable Intelligent Manufacturing
Open Data Lakehouse helps organizations run quick analytics on all data — structured and unstructured at a massive scale. It eliminates data silos and allows teams to collaborate on the same data with the tools they choose on any public and private cloud (Cloudera, 2023a).
This modern data architecture delivers data reliability with ease of data management. Run BI — Business Intelligence, AI — Artificial Intelligence, ML — Machine Learning, streaming analytics on the same data without ever moving or locking the data.
Moreover, the Cloudera AI platform is an open and extensible platform that efficiently harnesses all the data for foundation ML models and Generative AI. It enables lowering the TCO — Total Cost of Ownership, with a flexible hybrid platform that keeps model-training costs manageable even as data volumes grow.
Use cases for intelligent Manufacturing (Cloudera, 2023b) include intelligent operations, connected intelligent products, connected customer experiences, and connected supply chains.
Intelligent Operations
Intelligent operations enable manufacturing organizations to optimize their production operations, improve product quality, increase operational efficiencies, and predict asset failures to take action on time.
Intelligent Operations provide the visibility to predict and prevent equipment failure, remote monitor and control equipment, optimize energy usage, and maximize value from all manufacturing data in any format — including real-time data to achieve operational excellence, increase yield and accelerate business results.
Connected Intelligent Products
Connected products are at the forefront of the industry, literally reshaping the relationship between people and products. The connectivity these products provide drives customer satisfaction and revenue.
The ability to ingest, process and analyze IoT data is critical, as it enables the organization to capture data from various sources to see customer feedback and identify manufacturing issues.
Connected Customer Experiences
Companies are under pressure to stay competitive, and often, the question is how to take products to the next level. However, some of today’s most significant opportunities aren’t about products-they’re about enhancing customer experience.
Manufacturers are using analytics and machine learning to enhance the customer experience. A connected, dynamic manufacturing supply chain allows the manufacturers to respond better to customers with 24/7 insight into inventory and other variables. Taking real-time actions to minimize supply chain disruptions is imperative.
Connected Supply Chains
The supply chain is the lifeblood of the business. Its enemy? Disruptions and delays.
Innovative manufacturers are turning to real-time data, analytics, and machine learning to ensure their supply chains are fully functional and optimized end-to-end. Cloudera is making it easy for companies to leverage real-time data sources such as sensors, GPS, RFID, and clickstream with a modern data architecture that offers machine learning capabilities and the breadth of open source to power expanded analytic capabilities.
References
- Andi Sama, 2023, “Society 5.0,” https://medium.com/@andisama/society-5-0-professors-talk-summary-by-prof-dr-peter-cochrane-obe-d-sc-ac605ede3b6f.
- Andi Sama, Cahyati S. Sangaji, 2023, “Embarking on a Digital Transformation Journey to Industry 4.0 — Automation & Control,” https://medium.com/@andisama/embarking-on-a-digital-transformation-journey-to-industry-4-0-automation-control-258105fd590d.
- Cloudera, 2023a, “All your data. One Platform. Limitless possibilities.” https://www.cloudera.com/.
- Cloudera, 2023b, “Manufacturing. Now with higher intelligence.” https://www.cloudera.com/solutions/manufacturing.html
- Endeavour Business Intelligence, 2023, “Industry Insights: Data and Analytics Management,” https://www.cloudera.com/content/dam/www/marketing/resources/analyst-reports/industry-insight-the-state-of-data-and-digital-transformation.pdf?daqp=true.
