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Covid-19 is Creating a Perfect Storm for Manufacturing

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By Rafael Gomez, Director Product Strategy, Bright Machines

The pandemic’s economic impact started as a supply chain shutdown in Wuhan, China, but rapidly became a three-tier global disruption. As the virus spread, worldwide supply chain was interrupted, followed by an unprecedented shift in product demand and most recently by mandated factory shutdowns imposed on non-essential product manufacturing lines.

Let’s discuss the impact of these disruptions and explore how we can mitigate these forces that threaten to destabilize manufacturing.

Disruption #1 – Manufacturing and the supply chain

The first disruption to manufacturing and the associated supply chain was in China. This was due to the outbreak of novel coronavirus (Covid-19) forced workers in that county to stay home rather than return to work after the Chinese New Year holidays. The resulting impact was that a significant amount of the world’s manufacturing capacity was essentially shut down for an extended period, more than two weeks in most of China, and much longer in Wuhan.

This manufacturing and supply chain shutdown turned out to be just the start.  As the virus spread, manufacturing shutdowns rapidly spread throughout Europe and the US. We are now faced with the challenge to scale additional capacity or rapidly move production from one facility to another, neither of which are feasible in the manufacturing industry.

Disruption #2 –Demand volatility

Just as China’s factories started to come back online it became abundantly clear that the challenges were global and that certain products like PPE (Personal Protective Equipment) and medical devices were in unprecedented demand in terms of volumes and urgency. Meanwhile, workers, who are themselves consumers, were staying home and not shopping, sending economic shockwaves around the world, resulting in a dramatic downturn in market demand for non-essential or discretionary products. Add government and administrative intervention, including the loosening of FDA regulations and the use of the Defense Production Act in the USA, and it’s easy to see how the manufacturing industry was suddenly forced to deal with the unprecedented reactionary shift in market demand.

Disruption #3 – Workplace challenges

The third disruption came in the form of government directives to shelter in place and enforcement of workplace social distancing (including new OSHA guidelines).  Furthermore, non-essential factories have been shut down for an extended period. Once factories reopen, manufacturing plants will need to adhere to new and complex regulations. For example, when factories re-opened in China, they were mandated toto demonstrate ten-day supply of face masks for each worker. For example, a factory of 500 operators would need 10,000 masks to be authorized to continue operations. For many factories, an ongoing supply of PPEs in short supply and can be challenging and costly to obtain.

Once manufacturing companies receive authorization to restart operation, workplace social distancing on the factory floor will impact every discrete manufacturing function Traditionally, manual assembly lines are designed with minimum operator to operator spacing to facilitate the passing of product between stations and to minimize required floor space. With the new OSHA directives, these manual lines will need to be redesigned to increase operator spacing.  factories have met these challenges in creative style, like running extra shifts to redeploy staff and keep them distanced.

The data-haves and data-have-nots

Manufacturers that have embraced digital transformation, and the associated software-controlled automation, are best equipped to succeed in light of these disruptions. Real-time data drives visibility, which allows these “digital haves” to see the impacts of disruption sooner. Meanwhile, smart automation provides tools to adapt and adjust course quickly. Not only are these companies able to adapt production to meet increased demand or comply with new regulations, they are able to rise to the challenge of manufacturing the machines, devices, and consumables needed to help fight the virus, perhaps offsetting the loss of orders for ‘non-essential’ products.

The Future is agile and resilient

This perfect storm of disruption has exposed limitations of traditional manufacturing ecosystems and their associated supply chains. It has become clear that manufacturers need to move away from traditional analogue operational models, where production takes significant and costly time to set up on a line and requires constant tweaking or adjustment by experts with tribal knowledge of manufacturing processes.

To minimize the impact of economic disruption, manufacturers need to operate in a new paradigm.  This new version of manufacturing is fully data-enabled and software-driven to deliver an automated solution that provides the resilience to cope with disruption and the agility to react and adapt when that inevitable disruption occurs.

Considering previous viral outbreaks and natural disasters, Covid-19 isn’t the first global event to disrupt manufacturing and the supply chain, and it certainly won’t be the last. One key learning from this unprecedented event is that companies that have embraced digital transformation of manufacturing are the most robustly equipped to survive this economic disruption. These forward-thinking manufacturers will surely reap the prosperous benefits of their proactive digital transformation.

https://www.brightmachines.com/blog/

Designing User Experience for the Factories of Tomorrow

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by Olga Zinoveva, Senior Software Engineer, Bright Machines

The User Experience (UX) discipline in the technology sector has evolved rapidly over the last two decades and we’ve all witnessed the changes.  For example, the transition from button-based phones and keyboard-only interfaces to increasingly powerful yet easy-to-use, touch-based smartphones and tablets. A parallel change has been happening in factories, with industrial Human-Machine Interfaces (HMIs) evolving from physical push buttons, lights and switches in the 1980s, to the multi-touch screens of today. And we are not done evolving yet!

I have worked on various consumer applications in the past, including games and websites, and was directly responsible for building the UX on a couple of those projects. My experience in consumer UX gives me some insight into the many exciting opportunities that lie ahead for industrial UX. Here are a few I’ve been thinking of.

Defining UX in the factory context

In a setting where a vast array of hardware devices are connected to each other in complex ways, and users range from operators on the factory floor to project managers in remote offices, UX goes far beyond a single screen. Instead, it encompasses the full experience of using the system, from any interface or device that connects to it. Industrial UX is a mix of software (dedicated touchscreen panels or apps) and hardware (buttons, feeders) interfaces controlling the machines on the floor, monitors giving real-time status updates about the production line, and services generating reports based on data collected in the cloud over many weeks. Almost every component we build becomes a part of the user experience, so we must approach design holistically. Every software and hardware engineer, product manager, and data scientist must think like a UX designer.

Increased software capabilities mean increased complexity

The role and responsibility of software in manufacturing is growing rapidly. But with more software capabilities comes more UX complexity. As more tasks move from hardware to software – whether running on the device itself, in a local server, or in the cloud – the number of ways that users can interact with the system and their complexity increase. Yet the UX we build cannot simply hide this complexity from the users. A core concept of UX design is that people always form mental models of how a system operates, whether we want them to or not, and if their model sufficiently differs from reality, it will lead to frustration and mistakes.  Therefore, the next-generation factory UX will need to be intuitive and straightforward, but never oversimplified. The goal is to design a UX that helps users build the right conceptual models from the start to maximize productivity and minimize training time and mistakes.

The high bar set by consumer devices

Almost every worker in a modern factory has used a smartphone or tablet – this year, global smartphone usage is expected to hit 2.5 billion (and it’s growing)! As a result, today’s factory workers have a high level of technical literacy and familiarity with certain interaction standards. This represents an incredible opportunity for industrial UX because it can reduce training time for any UX that follows these standards. At the same time, the ubiquity of thoughtfully designed consumer devices has raised the bar for the quality of user interactions, responsiveness, and UX clarity in the factory context. Workers now expect industrial interfaces to work as well as their personal smartphones.

Building UX for the factory of tomorrow is no small feat, but it represents a massive opportunity and an exciting time for UX professionals as they help inform the next wave of industrial innovation.

An edited version of this article also appeared in Design World on June 3, 2019.

The Inevitability Of Software-Defined Manufacturing

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From 2003 to 2006, I worked at a contract manufacturing company as a robotics engineer. I was the first software engineer hired by the company, an opportunistic hire by a visionary CEO who saw the importance of automation in manufacturing. The CEO wanted to reduce downtime in manufacturing, improve quality, and empower the folks on the factory floor to be more efficient.

That period of my career was a fascinating experience. I was coming from a Fortune 500 energy company, where I had been a database programmer working with many highly capable engineers on scaling large data models. In that environment, continuous improvement through software automation wasn’t aspirational, it was our explicit mission. I took the role in manufacturing because I wanted the opportunity to define and deploy a software roadmap from scratch. I learned a lot during that time. As successful as the company was, software didn’t really exist inside the company, aside from an arcane enterprise resource planning (ERP) system that was poorly supported and badly used. I did everything from programming robots by hacking into them (APIs in manufacturing equipment didn’t really exist at the time, and still don’t), to developing web-based workflow software, to educating employees on how to use not only the tools I built, but software such as Microsoft Excel. Along the way, I discovered these existential truths, so to speak, as they applied to manufacturing as a whole:

  • Everyone saw the benefits of automation and wanted to automate as much as they could
  • Very few people understood the role software played in automation, even at the highest levels of the company

Fast-forward 16 years and much to my astonishment, manufacturing as a whole has not progressed. In learning about Bright Machines and our opportunity space, I encountered a lot of the same problems I faced 16 years ago. In manufacturing, the bulk of inspection remains largely manual. Instead of data being collected across the factory to be analyzed, it is mostly hostage to a particular machine, or worse, not collected at all. The concept of transforming data across the factory floor into actionable information that enables building higher quality products faster is at best an ambition. From designing a product to setting up a job, there is very little automation throughout the process of building physical products. In fact, setup and deployment take weeks, sometimes months, leading to significant product delays. That’s just the beginning of the list of problems with manufacturing today. It’s a very long list indeed.

When we compare manufacturing to other industries that have not only embraced technology, but pushed its boundaries to innovate and succeed, we can’t help but wonder why this key economic pillar remains stuck in time. I posit that this is for several reasons. Manufacturing is a demand-driven industry with low margins. For most manufacturing companies, it has simply been easier to throw humans at any given problem, knowing that labor costs can be scaled up and down based on demand. At first blush, the calculation seems rational. Investing in sophisticated hardware powered by equally sophisticated software at an industrial scale carries a lot of expense, not only in upfront costs, but maintenance, ongoing upgrades, support, and so on. Then, there’s the problem of time. Customers want things manufactured quickly. Who has time to invest in equipment set up, calibrating machines, setting up networks, securing the data, etc.? Human workers, on the other hand, can be deployed on an as needed basis.

Except that things really don’t work this way anymore. Humans, rightfully so, decided they are no longer willing to work in arduous and monotonous jobs, leading to reports of “voluntary turnover rates exceeding 300%” in some parts of the world. That is an astonishing statistic. The cycle of innovation in industry has evolved and sped up so much that having the ability to not only deliver product in near-real time, but perform meaningful reactive as well as predictive data analysis is an absolute must in order to operate efficiently in manufacturing. The increasing sophistication of the products being developed require the precision of machine automation and the power of not only software, but artificial intelligence, for higher product quality and predictability.

Which brings us to today. Manufacturing is crippled by these pain points, but ill equipped to solve them, for the same two fundamental reasons I encountered 16 years ago: manufacturing companies certainly understand the value of automation but have not historically utilized software to implement automation. Manufacturing companies are, after all, not software companies. And until now, the lack of demand for software-defined manufacturing has led to few external companies that are actually positioned to deliver holistic software solutions that act as both immediate relief as well as business accelerators to manufacturing companies. Thus, we are at a critical inflection point where manufacturing as an industry is not only ripe for disruption, it is virtually begging to be disrupted in order to save itself.

So what does disruption look like in this space? In fact, what is software-defined manufacturing, really?  Is it artificially intelligent robots? Is it data platforms with state of the art business intelligence? Is it cloud-based platforms, remote deployment and troubleshooting, machine-learning driven analytics? These things definitely comprise the concept, but Software-Defined Manufacturing is really just the beginning.

Software-Defined Manufacturing will happen simply because it has to – it is the immediate cure to manufacturing’s already existing pain points. The true disruption in manufacturing will involve not disrupting manufacturing per se, but actually disrupting the very idea of software-defined manufacturing itself. And it will happen by industrializing all the technologies that make up software-defined manufacturing, deploying them as a scalable platform and delivering them to customers in a service-based model that grows and modulates with the needs of the business. True disruption is extending software-defined manufacturing to a hardware/software ecosystem, with minimal to nonexistent single points of failure, where multiple components work harmoniously with the single purpose of enabling fast, high quality delivery at lower cost; where data is assembled, collected and turned into predictive analytics, and artificial intelligence is effectively used to solve repetitive human tasks.

When will this happen? At Bright Machines, the call to innovation has been answered, and the transformation in manufacturing has already begun. For us, software-defined manufacturing is just the beginning, the building blocks of delivering an ecosystem of products that will not only disrupt but redefine an entire industry. It’s an extraordinary challenge and truly a generational opportunity. And it’s Day One of our own journey to change the world.

— Nick Ciubotariu, SVP software engineering, Bright Machines