Industry 4.0 is enabling new concepts and technologies that make factories smarter. It begs the question: how do we create stronger synergies between humans and machines to improve production efficiencies, while progressing the creative cognition of human potential?
This question gained traction after the global pandemic. The industry started to emphasize socio-technical considerations to enable new use cases around asset management, workplace well-being and process control, requiring ambient computing at the manufacturing edge.
What Is Ambient Computing?
Ambient computing is a form of ubiquitous computing, a subset of edge computing. It uses computing power to exhibit human-like intelligence in perceiving, processing and taking actions based on available data and information.
In simple terms, ambient computing enables a smart agent – think of an Alexa and Siri optimized for manufacturing processes – to collaborate with people, operational technologies and assets, such as machines and autonomous mobile robots, to mitigate disruptions at the manufacturing edge. The manufacturing edge reflects a location of an industrial organization where massive quantities of data are created, analyzed and acted upon in near real time.
Bringing ambient computing to the manufacturing edge can help create an IT environment where operational technology (OT) personnel collaborate with AI-driven agents to address alerts and schedule events, as well as identify and mitigate risks and issues. The fusion of AI into the manufacturing edge also helps drive continuous improvement and introduces innovation of new products and services.
Working with People, Assets and Processes
Ambient computing lets organizations focus on growth and innovation by bringing agility to the manufacturing edge where people, assets and processes are working together in unison to deliver required yield and throughputs.
Ambient computing can be applied to the following examples:
- Assets monitor themselves and schedule maintenance based on wear and tear.
- A smart meter system (water, air, gas, electricity and steam) manages the production environment to reduce waste and drive efficiencies by automatically adjusting its end devices such as thermostats and valves.
- Automated guided vehicles and mobile robots self-manage routes and tasks based on product, people and environment.
- Production and assembly floor environments monitor themselves to ensure safety and security of people, products and assets.
- Smart devices such as notebooks, phones, tablets, wearables and stand-alone devices collaborate with people on risks, issues, continuous improvement and production optimization.
By transforming the manufacturing floor to be automated and self-sustainable, ambient computing can reduce operational costs, improve product quality and time-to-market and empower employees to work smarter. With access to real-time information, organizations can improve how they handle market and ecosystem disruptions with better and faster collaboration between humans and systems.
Adopting Ambient Computing
Organizations need seven core elements to realize ambient computing, foster data availability and increase collaboration among people, applications, assets and devices.
1. Edge computing to enable real-time decision-making and collaboration: Compute and storage resources exist closer to where data is generated and communicated to improve processing and response times at the manufacturing edge.
2. Data-as-a-service to meet changing needs: A data platform that uses data mesh and data fabric to enable data as a service to meet the needs of manufacturing edge from acquisition of data-to-data availability.
3. Digital twins for predictive insights: A virtual representation of a composite environment representing individual elements of assets, processes, systems, smart devices and services that mirror the manufacturing edge. Digital twins enable a representation of past and present scenarios at the manufacturing edge to predict futures and take actions.
4. Cognitive automation for self-learning: Cognitive automation uses AI and its underlying technologies such as machine learning, generative AI, natural language processing, speech and object recognition to allow self-learning at the manufacturing edge.
5. Connectivity to support constant communication: It is important to set up a network for reliable data communication to meet the service level needs of assets, systems, devices and services in a secure way. It can be deployed in a combination of ways such as ethernet, 5G, wireless and sensor-driven communications tailored to the given environment.
6. Quality of experience (QoE) to meet diverse needs: QoE is a measure of satisfaction by a user when collaborating with an ambient computing environment at the manufacturing edge. QoE is a critical part of ambient computing from conceptualization to deployment, considering diversity in the workplace.
7. Trusting systems to perform: The Industrial IoT (IIoT) consortium defines trustworthiness as “the degree of confidence one has that the system performs as expected. Characteristics include safety, security, privacy, reliability and resilience in the face of environmental disturbances, human errors, system faults and attacks.” Successful ambient computing relies on the trusted relationship between humans and machines.
There are other technology considerations organizations can adopt to complement the seven core strategic elements, including cloud computing, AR/VR and the Metaverse.
Ambient computing is an enabling concept with related technologies that are helping drive Industry 4.0 to develop smarter factories. It is gaining momentum among researchers and early adopters in global technology, retail goods and automotive manufacturing, and can have a transformative impact across other industries, including life sciences, energy and smart cities.
This article considers the production environment, however ambient computing can be deployed as a point-based solution to address a specific process area or production line or to collaborate with an asset such as a collaborative robot.
Ambient computing can help organizations realize many positive workplace outcomes – from reducing operational costs and optimizing processes, to human creativity and innovation at manufacturing's edge.
Madhu Gaganam is an engineering technologist and manufacturing domain architect for edge portfolio solutions at Dell Technologies.
