Intelligence at the factory edge: Boost productivity and improve costs

Update: May 25, 2021

As factories strive to boost productivity and improve operational costs, the demand to deliver new technology that empowers intelligence at the edge is increasing. For those of you asking yourself what “the edge” means, at Maxim, we define “the edge” as where the machine meets or interacts with the real world.

Empowering intelligence at the edge in factory automation means reducing the amount of lost productivity that a factory experiences in a year. So what does it take to empower intelligence at the edge?

It takes a new way of thinking.

As Semiconductor suppliers, we need to deliver solutions that enable intelligent sensors and actuators, support software-configurable I/O, and provide advanced diagnostics. Let’s review the importance of these four critical elements and the key capabilities they provide in empowering intelligence at the edge.

Intelligent sensor technology
Sensors are found everywhere! They have become ubiquitous in our everyday lives. In the manufacturing environment, all manufactured products require an array of sensors that work in unison to help machines detect an object, determine the distance to an object, configure the colors and composition of an object, and monitor the temperature and pressure of an object or liquid.

Commissioning new sensors to replace damaged sensors or adapting a piece of equipment to enable the manufacturing of a different product is labor-intensive and contributes a significant cost burden due to lost productivity. The cost of sending a technician to the factory floor to change a sensor and then recalibrate it to the correct manufacturing parameters impacts factory throughput. If we multiply this same level of maintenance for every sensor across a factory, changing or reconfiguring a sensor is the single-most expense that all manufacturing lines incur.

IO-Link is an exciting new technology that allows intelligent sensing all the way down to the machines on the factory floor. This new technology enables flexible manufacturing to improve factory throughput and operational efficiency. This technology converts traditional digital or analog sensors into an intelligent sensor by providing bidirectional information exchange with the sensor. It adds a new level of intelligence and capability to remotely commission the sensor as well as the ability to react in real time by making on-the-fly adjustments to the sensor parameters.

Industrial automation machinery now has a newfound intelligence to dynamically respond to real-time operating conditions based on the health and status of a network of sensors located across the factory floor. By tapping into this sea of end-to-end information across a network of intelligent sensors, a facility can create a mapping of its factory floor to provide better real-time information to an overarching artificial-intelligence monitoring solution that can rapidly identify manufacturing bottlenecks and points of failure as well as provide a new capability to optimize the entire factory floor for better operational efficiency.

The way that IO-Link technology simplifies the commissioning process and improves factory throughput is by making sensors interchangeable through a common physical interface that uses a protocol stack and an IO Device Description (IODD) file. This allows technicians to quickly commission a sensor, which results in reducing factory downtime and allowing the manufacturing line to be reconfigurable on the fly.

IO-Link hub and software-configurable I/O
While it’s clear that IO-Link technology is the catalyst behind a set of new intelligent sensors, it is also providing new opportunities that bring intelligence to the edge through IO-Link hub solutions. These new IO-Link hubs provide a simple way to add analog and digital I/O expansion channels as well as the integration of intelligent actuators such as solenoid and motor drives.

The IO-Link hub provides a simple way to expand the types and number of channels needed to support unexpected manufacturing line reconfigurations. These IO expansion hubs provide a solution that leverages all the benefits of IO-Link technology and simplifies the task to add digital and analog I/O ports. This new class of products enables the commissioning of the sensors via the IO-Link hub, which reduces factory downtime. Examples of these solutions include Omron’s IO-Link Hub NXR product family, which achieves a 90% reduction in setup and commissioning times.

Software-configurable digital and analog I/O solutions allow automation engineers and technicians the convenience of providing a universal I/O port that can be commissioned remotely. Comparable with the benefits that IO-Link provides, this new class of digital and analog software-configurable I/O products simplifies a factory’s wire-marshalling burden and provides flexibility to physically connect any digital and analog I/O sensors or actuators to any unassigned digital and analog I/O port. This software-configurable technology is more cost-effective and increases the channel density on the factory floor.

Omron’s NXR-Series IO-Link controller and IO-Link I/O hub with the MAX14918, MAX14827A, and MAX14912/15 (Source: Maxim Integrated)

Intelligent actuators
Actuators are used to influence and control the direction and speed that a product moves across the factory floor. Because all applications require a unique set of motion control and motor drive characteristics, these smart actuators will need to dynamically adjust to their environment to form that perfect mechatronic cyber-physical system.

Currently, intelligent actuators are evolving to provide an auto-configuration capability that autonomously adjusts its performance parameters to meet the demands of its operational environment. This is the first step in making the actuator become self-aware of its environment and allow the system to optimize its performance for maximum throughput or to maximize the long-term reliability and operational performance of the actuator. In either case, the result yields lower operational costs and higher efficiency.

To empower this combination of intelligent motion, it requires the integration of two key elements.

The first critical element is power-efficient analog-drive technology to allow high-voltage operation while providing the health and status of the local environment to enable optimization of the motors and to achieve a balance between high efficiency and faster throughput.

The second critical element is the ability to provide motion control algorithms to enable a smooth range of motion. This consists of the ability to detect loads placed on the motor during operation to avoid line failures and to minimize power consumption.

Motion control algorithms provide smooth and precise movement, while the chopping algorithms focus on making the motor more power-efficient. In addition, sensing the position of the armature is important to know if the motor has moved to the correct position. This is done with magnetic sensing, typically using Hall sensors or some type of optical encoding solution.

To demonstrate the value of these next-generation intelligent actuators, here are two new examples: the PD42-1-1243-IOLINK and the recently released End-of-Arm Tooling (EOAT) gripper reference design, the TMCM-1617-GRIP-REF. Both solutions demonstrate the power of combining intelligent motion, the driver, and IO-Link communication technology.

These intelligent actuators simplify commissioning and boost factory productivity by providing the industrial automation engineer access to 50% more configuration and performance parameters over the IO-Link communication interface. In addition, these intelligent actuators can be adjusted on the fly to accommodate changes in operating environment and to implement advanced AI-derived productivity solutions. This ability to shape the actuator’s performance based on its operational environment is the future of intelligent motion control.

End-of-Arm Tooling (EOAT) gripper reference design, the TMCM-1617-GRIP-REF (Source: Trinamic)

Diagnostics and real-time decision-making
Higher levels of diagnostic capabilities continue to provide a richer dataset that improves real-time, edge-based decision-making to improve productivity and operational integrity on the factory floor.

These powerful manufacturing-based AI algorithm platforms are expected to grow from $1 billion in 2018 to over $17 billion by 2025, or at a compound annual growth rate close to 50%, according to a 2019 MarketsandMarkets report entitled “Artificial Intelligence in Manufacturing Market.” During this time, machine learning is expected to be the highest growth segment in AI due to the rapid investments being made to implement smart factories.

The driving force behind this growth stems from the abundance of health and status information being generated from a network of IIoT-powered devices, algorithms providing predictive analytics, and machine-vision cameras monitoring the quality of products as well as evaluating the status and operational health of the machines.

At the IC level, more and more information is being monitored, collected, and communicated via the SPI bus to and from a microprocessor. The volume of these IC datagrams continues to multiply as they carry critical information such as temperature status of a device, overvoltage, overcurrent, open-wire detection, short-circuit detection, overtemperature warnings, thermal shutdown, and CRC.

If we take a step back now and multiply the number of semiconductors providing datagrams across the entire breadth of equipment on a factory floor, it becomes clear that a diagnostic mapping of the factory floor can be achieved to anticipate, identify, and diagnose manufacturing line failures.

The next big thing
One thing is clear: By empowering this “new way of thinking,” smart factories can take advantage of these new capabilities to improve throughput and increase productivity. As these new technologies continue to mature, the next generation of AI algorithms will become the beneficiaries by leveraging the higher quality of real-time data being generated from these solutions.

As a result, these new self-aware capable machines will automatically implement AI-generated solutions to keep a manufacturing line operational until it is repaired or serviced by a technician. This era of self-aware machines will inspire the next big thing in industrial automation.

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