The promise of Industry 4.0 conceptualizes rapid changes in technology and operating processes. Today, interconnectivity through cyber-physical systems and efficient data harnessing assumes central focus across industries. This holds especially true in the manufacturing industry, giving rise to smart manufacturing in smart factories.
Before we delve deeper into what organizations need to do to disrupt their processes and secure a firm footing at the forefront of innovation, a conceptual understanding of smart manufacturing is essential. Smart manufacturing is a technology-driven approach to manufacturing that adopts the Industrial Internet of Things (IIoT) – an extension of the Internet of Things (IoT) in industrial sectors and applications. With a strong focus on machine-to-machine (M2M) communication, big data, predictive maintenance, and machine learning, IIoT enables industries and enterprises to promote enhanced efficiency and reliability in their operations. The IIoT encompasses industrial applications such as industrial robotics, medical equipment operations, and software-defined production processes.
The advent of IIoT-driven smart manufacturing envisions a production environment with a fully automated and intelligent network of systems that facilitates machines, facilities, and logistics chains within the manufacturing plant to be managed with little to no manual intervention. In other words, the establishment of a smart factory. The active exchange of data between production tools, machines, and all elements within the production technology chain through embedded sensor systems, fuels machine learning to optimize operations by boosting efficiency and realizing more savings continually. Additionally, the associated benefits for organizations adopting smart manufacturing technologies are as follows:
The growing awareness of smart manufacturing and its associated benefits have characterized a paradigm shift in the manufacturing market. According to Fortune Business Insights, the global smart manufacturing market is expected to grow from USD 277.81 billion in 2022 to USD 658.41 billion in 2029 at a CAGR of 13.1%. Global manufacturers recognize that the next generation of robotics and automation technologies within the ambit of smart manufacturing will have an unprecedented impact on manufacturing in terms of productivity, quality, safety, and cost metrics. According to Cisco, machine-to-machine (M2M) connections that support IoT applications account for more than half of the world’s 28.5 billion connected devices. Interestingly, the largest market share of smart factories is held by APAC countries with China and Japan leading the way.
A recent study by Forbes found that enterprises invested an annual average of 3.24% of their revenue by building 40% more smart factories over the last three years, almost 1.7 times higher than the amount invested between 2016-2019. As of 2021, smart manufacturing technologies have made a foray into most production-defined industries.
While the benefits and impact of smart manufacturing on overall process visibility, productivity, and cost efficiency are evident, enterprises need to gain a comprehensive understanding of their manufacturing operations, business models, and supply and logistics chains. The findings of these assessments are essential to evaluate whether the establishment of a dynamic production environment such as a smart factory is suitable for them.
Let’s understand it better with an implementation by Quantiphi for one of the largest food manufacturers in the United States.
One of our customers, an American Fortune 500 branded consumer foods manufacturer, wanted to solve critical issues related to their machine process data accessibility and storage.
The customer faced significant challenges in the utilization of their available machine process data within their existing systems. In particular, insight generation from their cheese-making lines was unstructured, leading to a lack of optimization of their processes. Further, the customer’s storage systems were primarily focused on an on-premises storage strategy and required them to be streamlined with cloud storage options.
In order to address these challenges, Quantiphi leveraged Google’s Intelligent Manufacturing Data Engine.
Google’s Intelligent Manufacturing Data Engine (iMDE) is a contemporary solution that provides a two-pronged approach to smart manufacturing implementation – data analytics and AI-driven operational optimization. Manufacturing analytics and insight generation are facilitated by the iMDE API through Factory Connect, data processing, contextualization, and integration with other Google Cloud Platform services. Relevant use cases like visual inspection, machine-level anomaly detection (identification of red, yellow, and green statuses for equipment based on sensor data and failure metrics), predictive maintenance, root cause identification, and inline quality control are driven by iMDE’s AI-driven operational optimization capabilities. Additionally, iMDE is capable of supporting a variety of data formats from telemetry to images.
Quantiphi’s solution was designed to be capable of connecting multiple production lines across multiple site areas and locations with minimum hassle. Various Intelligent Manufacturing Suite components were installed on the Google Cloud Platform and a pipeline was built to fetch streaming data from the factory connected to BigQuery without changes to the existing system. Quantiphi also implemented Whistle Data Transformation Language to transform JSON input data into data that can be transmitted through Dataflow pipelines. This implementation loads these records to a BigQuery destination to offer insights on data pushed from their manufacturing equipment. Dashboards were built to visualize these insights – Looker for near real-time data analytics of cloud data and Grafana for on-prem data. With future enhancements in mind, Quantiphi also included the Intelligent Manufacturing Suite.
By embracing smart manufacturing technologies, manufacturers can scale new heights in productivity, efficiency, cost savings, and overall facility visibility. Through smart manufacturing, manufacturers can expect higher throughput, dramatically improved uptime, and lower operating costs. In essence, implementing new technologies to improve existing processes will optimize the supply chain. Innovation is risk mitigation to ensure enterprises not only succeed in a competitive and volatile landscape but also grow.
Get in touch with us to transform your operations with smart manufacturing and maximize productivity and cost savings.