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Deploying the Factory of the Future to solve production problems of the present

19 August 2019 Alex West

Any manufacturing enterprise planning to become the "Factory of the Future" should start by thinking of the myriad challenges makers and producers face today. While a host of innovative technologies at present promise nothing less than a revolution in the business of fabricating goods, a clear understanding of fresh or novel mechanisms is needed to allow their intelligent integration into current manufacturing practices.

Ultimately, however, new technologies like augmented and virtual reality, robotics, artificial intelligence, and the Cloud will succeed or fail depending on their ability to address the pain points and challenges now confronting manufacturers. These challenges include retaining skills and talent, improving productivity and reducing downtime, ensuring worker safety, and bolstering manufacturing flexibility and speed-to-market.

The sections that follow discuss these challenges in greater detail, along with their possible resolution through the Factory of the Future.


Challenge 1: Skills and people retention

Advanced technologies like robotics and artificial intelligence have raised concerns that machines could potentially replace the human workforce. For the short term, however, there is little apparent need to worry. With US manufacturing unemployment rates currently low at 3.0%, according to the US Bureau of Labor Statistics, the bigger challenge in industry isn't the potential fallout from a layoff or workplace reduction, but in finding enough workers and in attracting new blood to replace retiring baby boomers.

The cost of a retiring workforce goes far beyond finding a replacement. According to the Mellon Financial Corporation, between 1.0% and 2.5% of the total revenues of a company are lost because of decreased productivity stemming from new hires and the learning curve involved.

The Factory of the Future solution:

Augmented Reality (AR) can help address the challenge of knowledge-sharing within an organisation and of supporting less skilled workers by providing on-the-job support, training, and even remote assistance. Mixed Reality (MR) solutions could also be helpful by combining Augmented and Virtual Reality to let users navigate both real and artificial spaces at the same time.

Through AR, engineers fixing equipment can access user manuals through a head-up display and follow step-by-step procedures, freeing their hands for more important work than to turn pages. Workers can also be equipped with specialized glasses incorporating an audio link and a camera allowing live streaming, all the while enjoying real-time support from off-site engineers.

In the case of Lockheed Martin, the Maryland-based aerospace firm has trialled AR solutions to produce its F-35 fighter planes. Company engineers were equipped with educational software hosted on AR glasses that showed not only how the fighter plane's different parts fit but also the part numbers associated with the plane's components. The result was a 30% improvement in productivity, enabling engineers to work faster with just minimal training.


Challenge 2: Increasing productivity and reducing downtime

While many new technologies can be introduced in the name of boosting efficiency, cost remains king and will ultimately dictate purchasing decisions and a company's bottom line. Such decisions are often based on a short payback window spanning less than a year in time, rather than on the total cost of ownership (TCO).

Machine and equipment failures can be especially costly with unplanned downtime, running into the tens of thousands of dollars per minute. Other aggravating factors—the cost of repairing the failed part, or the damage caused to associated pieces of equipment—could add to the total financial tally. As a result, technologies capable of reducing unplanned downtime can provide a quick and tangible payback.

The Factory of the Future solution:

Predictive maintenance and condition monitoring applications can be of immense value. Supported by the increased access to data collected from manufacturing equipment, they enable the monitoring of a machine's performance to determine if it is deviating from accepted readings in parameters like vibration and temperature. As values stray from the norm, algorithms can be used to analyse the risk of failure and even the time frame in which a failure may occur. And with relevant data stored onsite as well as in the Cloud, comparisons can be made against previous asset failures to improve the accuracy of identifying imminent faults.

Advanced notification of an asset's potential failure not only provides companies with the tools to reduce unplanned downtime, the information can also be used to create smarter maintenance schedules, enabling maintenance teams to focus on the degraded equipment alone. Smarter repair and replacement can lower expenditures, with analytics deployed intelligently to identify which parts to replace and which ones to keep.

Utilizing predictive maintenance to monitor the health of assets is clearly a positive application—the low-hanging fruit, so to speak—of the industrial IoT, with a quick payback on investment that can be expected.

Predictive maintenance is, in fact, the top IoT-related application among organizations in their use of the Cloud, as shown in the chart below.

IHS Markit graphic on survey results of cloud-based analytics


Challenge 3: Worker safety

Plenty of manufacturing jobs exist today that ideally should not involve human labour. The 4D's of unwanted labour conditions include:

  • Dull - tasks, such as jobs with a highly repetitive component
  • Dirty - environments, characterized by extremes in temperature, smells, noise levels, and unpleasant substances.
  • Dangerous - conditions, in which operation of certain types of equipment or exposure to environmental elements could result in injury or loss of life
  • Demanding - jobs, where intense or protracted exertion—physical or mental—is required

The Factory of the Future solution:

Many specific technologies are already available to help reduce risk at the workplace and improve the safety of workers.

For instance, while robotics has long been used in the automotive industry to improve productivity and reduce worker risk in dangerous tasks, robots on their own can also introduce risk through malfunctioning or while interacting with a human worker. For this reason, collaborative robots—or "cobots"—were developed. Equipped with sensor skins sensitive to pressure, cobots will stop or reverse course during collision with a human worker. Today, cobots can work alongside humans without the need for additional safety equipment or zoning.

Other robotic solutions to improve worker safety include drones and "spider robots," which can navigate and operate in hazardous and difficult-to-reach areas. In the oil industry, such automated robotic solutions have been tested for monitoring flare stacks or fires around an offshore rig. Combined with on-board monitoring gear equipped with machine vision, the solutions can check for corrosion, cracks, and leaks more safely and more accurately.


Challenge 4: Responding to customer needs

An increasingly discerning customer base is challenging manufacturers to redefine how to do business and respond to customer needs. Manufacturers today are called upon to meet rapid shifts in market demand, drive product innovation, reduce time to market, and boost flexibility in the manufacturing process. Companies both large and small must be nimble not only in identifying market movements but also in forging new and high-quality products to either defend an existing position or to obtain first-mover advantage in a new area.

For manufacturers, meeting customer needs can present dual challenges: shortening the time in new product introduction (NPI); and building in customer preferences to support mass customisation while maintaining manufacturing economies of scale.

The Factory of the Future solution:

For faster time-to-market, a digital twin or model of a physical product can first be developed, and then tested and adjusted quickly if needed. Through simulation, prototypes can be subjected to real-world conditions to ensure or improve quality, shortening the time to move from concept to release.

In product customisation, companies can offer tailored goods and integrate customer-selection criteria with manufacturing, a process made possible by the seamless transfer of data from the point of sale to the factory floor. Successful execution will necessitate the deployment of connected enterprise and operational networks together with more flexible manufacturing processes, helped along by increased levels of automation that can adjust the manufacturing parameters of individual orders.


The central question, answered

Regardless of the manufacturing challenge in question—whether the issue is about improving productivity, promoting more flexibility on customer needs, or providing better working conditions—the technologies in the Factory of the Future will succeed based on their ability to meet the specific challenges of each industry and company type.

Ultimately, the central question confronting the Factory of the Future is one of monetization and revenue generation from the Industrial IoT. The answer can be found in those solutions able to demonstrate a clear business benefit and successfully deliver a quick return on investment.


Alex West
is research and analysis associate director for discrete automation and switchgear at IHS Markit
Posted 19 August 2019

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