DIGITAL SPECIAL ....The next horizon for industrial manufacturing: Adopting disruptive digital technologies in making and delivering PART I

The next horizon for industrial manufacturing: Adopting disruptive digital technologies in making and delivering PART I

The key to continued performance and productivity improvement for advanced industrial companies is the use of disruptive technology in the manufacturing value chain.

In the past few years, advanced industrial companies have made solid progress in improving productivity along the manufacturing value chain. In the US, for instance, the productivity of industrial workers has increased by 47 percent over the past 20 years. But the traditional levers that have driven these gains, such as lean operations, Six Sigma, and total quality management, are starting to run out of steam, and the incremental benefits they deliver are declining.

As a result, leading companies are now looking to disruptive technologies for their next horizon of performance improvement. Many are starting to experiment with technologies such as machine-to-machine digital connectivity (the Industrial Internet of Things, or IIoT), artificial intelligence (AI), machine learning, advanced automation, robotics, and additive manufacturing. The impact of this shift is expected to be so transformative that it is commonly referred to as the fourth industrial revolution, or Industry 4.0.

This new wave of technology and innovation offers companies opportunities not only to drive a step-change in productivity and efficiency, but also to capture strategic business value by establishing competitive advantage in the way they operate their entire “make to deliver” value chain. The nature and scale of the opportunities will vary from sector to sector and company to company, depending on factors such as value drivers, market dynamics, and operational maturity. However, we routinely see successful technology-enabled transformations dramatically shifting individual value drivers. For example, an aerospace manufacturer with a reputation for high quality but suffering from high labor costs and slow production implemented augmented-reality work instructions for complex assemblies to decrease error rates from 3 percent to nearly 0 percent while increasing productivity by 2530 percent. Similarly, an auto manufacturer that needed to maximize its already highly automated process began analyzing available data for micro-losses in capacity to unlock an additional 3 percent of overall equipment effectiveness. Finally, an electronics manufacturer operating in a high-cost country virtually eliminated material handling labor using automated vehicles for material delivery and robots for palletizing.

For companies that aim well and execute effectively, the resulting cost reductions could be transformational. We estimate that productivity gains and cost savings alone could deliver near-term impact of 200 to 600 basis points of margin expansion across advanced industries, worth $200 billion to $500 billion (Exhibit 1). In the mid- to long-term, even more value could be unlocked through greenfield plants, network reconfiguration, and upgrades to core IT and operating-technology (OT) architecture.

Exhibit 1 SEE THE ORIGINAL ARTICLE

Substantial though these cost reductions are, we expect them to be overshadowed by new revenue opportunities arising from increased speed to market, product customization, and new services. How much strategic business value they will generate remains to be seen, but we can expect the lion’s share of it to go to first movers.

Unlocking the value

To capture the value of digital in manufacturing and throughout the supply chain, leading industrial companies are developing use cases in three main areas: connectivity, intelligence, and automation (Exhibit 2).

Exhibit 2 SEE THE ORIGINAL ARTICLE

Connectivity

After rapidly expanding through the Internet of Things, connectivity has reached global scale, extending to some 8.4 billion connected devices. The ability to link digital devices—shop-floor monitors, remote computers, smartphones, tablets, and so on—to IT platforms and systems enables decision makers to access a flow of relevant information in real time. In production environments, only 15 percent of assets are connected as yet, but change is taking off. Advanced applications now being introduced in industrial manufacturing include digital performance management and the use of augmented-reality smart glasses to communicate instructions and standard operating procedures. In the supply chain, parts are being tracked digitally across supplier networks, and trucks are providing real-time data to enable just-in-time delivery, optimize work planning, and minimize inventory. The technology industry is working on more than 700 IoT platforms for industrial use, and major tech companies are investing heavily in platforms that extend beyond individual companies to whole industries.

One aerospace company struggling with supply issues combined data from purchasing, part tracking, and inventory monitoring in a single platform to enable real-time visibility of each part across the entire supply chain. The results exceeded expectations, with a 20 percent improvement in procurement productivity and a 5 percent improvement in on-time delivery. Another aerospace company took part traceability to the next level by introducing digital tagging. Parts were automatically scanned for minute differences in surface texture at key points in the supply chain, virtually eliminating counterfeiting and ensuring regulatory adherence.

Intelligence

Advanced analytics and artificial intelligence can be applied to large data sets to generate new insights and enable better decision making in predictive maintenance, quality management, demand forecasting, and other areas. Machine-learning algorithms are growing more powerful as computing power advances and big data proliferates. However, the full potential of artificial intelligence has yet to be captured in production environments, which at present use only a small fraction of data for decision making.

One auto manufacturer had difficulty managing growing complexity in its product variants, and sought to improve and automate its decision making. To do so, it installed an enterprise manufacturing intelligence (EMI) system that ingested data from more than 400 IoT sensors, enabling predictive intelligence to be applied to maintenance, quality, and parts supply. Introducing the new system improved overall equipment effectiveness by 10 percent and first-time-right delivery by 15 percentage points.

Flexible automation

Robotics and automation have been commonplace in industrial manufacturing for decades, but we are seeing a new wave of opportunity driven by declining technology costs, growing functionality, and an expanding range of environments in which robotics can be safely and effectively deployed. Introducing new robotic technologies in product assembly, warehousing, and logistics can improve the productivity, quality, and safety of operational processes. Applications include autonomous guided vehicles in distribution centers, automated warehouse management systems, and cobots (collaborative robots) working on assembly processes in conjunction with humans. Estimates suggest that 60 percent of manufacturing tasks could be automated, but industrial robots have yet to achieve widespread penetration even among early adopters. South Korea, for instance, has only 530 robots for every 10,000 production workers.

Deploying automation across the entire product assembly process from material handling to quality testing and packaging enabled one electronics company to reduce direct and indirect labor costs by more than 80 percent. These savings in turn allowed the company to manufacture its product in higher-cost countries located close to attractive markets, thereby reducing shipping costs while increasing customer responsiveness and speed to market.

Examples of what connectivity, intelligence, and automation might look like at an aerospace manufacturer are illustrated in Exhibit 3.

Exhibit 3 SEE THE ORIGINAL ARTICLE

Overcoming pilot purgatory

McKinsey’s research shows that most advanced industrial companies are conducting pilots in all three of these areas (Exhibit 4). In the aerospace and defense sector, for example, all of the top 10 companies and two-thirds of the top 50 have announced digital initiatives of some kind. Most of the business leaders we spoke to recognize that technology can help them navigate complex risk and regulatory environments, make their operations more efficient, and enhance the customer experience they offer.

Exhibit 4 SEE THE ORIGINAL ARTICLE

However, advancing beyond the pilot phase is still a big challenge for most manufacturing companies. Even among those reporting significant numbers of pilots, most struggled to achieve broader rollout. In fact, the gap between piloting and rollout is considerably larger than that between perceived relevance and piloting, suggesting that scaling is a bigger hurdle than getting the ball rolling in the first place (Exhibit 5).

Exhibit 5 SEE THE ORIGINAL ARTICLE

By Kevin Goering, Richard Kelly, and Nick Mellors

https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/the-next-horizon-for-industrial-manufacturing?cid=other-eml-alt-mip-mck-oth-1811&hlkid=4677593a878646529137da15dd8100cb&hctky=1627601&hdpid=40950bab-bdef-4ff9-9eb4-9ea21456999b

CONTINUED IN PART  II