DXC Technology has led three pioneering examples of Smart Connected Manufacturing, which I first introduced at Discover London 2016. Each of these next-generation manufacturing pilots achieved not only the intended proof-of-concept for customers, but also revealed — and delivered — much greater, additional value in the process: predictive maintenance and remote, smart robotics proved transformational in these cases.

The three examples flow from the mission that  DXC Technology embarked on three years ago to understand the relevance of digital to the manufacturing sector. During our learning mission we gained a deep understanding of technology, market and business drivers. How the enhanced complexity of supply chains was moving towards a fluid value network, and the fact that the consumer is dictating many future moves and demands.

Each of the use cases I detail below arose out of this learning, led by the need of the customer, and with the digital response fashioned by DXC alongside the manufacturing customer.

Zeiss creates revenue opportunity out of efficiency drive

Zeiss, the German manufacturer of optical lenses and eye glasses, was experiencing a certain failure rate in its lens production. It enlisted  DXC Technology as a partner to utilise digital techniques of real-time data and analytics to analyse how to reduce the failures and increase efficiency.

Carl Zeiss Vision Care produces a large variety of spectacle lenses every day and throughout the product cycle, several challenges may arise:

  • Lenses may require multiple passes through the production cycle, resulting in additional production costs for each lens.
  • Lens parameters such as surfacing, tinting, coating, edging and finishing are defined with order entry.
  • Differences in lens geometry, machine behaviour, shift variances and suppliers need to be taken into account.

In order to reduce the number of passes needed to manufacture lenses, Carl Zeiss and turned to data analytics, utilising data generated throughout the entire production process.

We proposed a solution to collect, measure and intelligently analyse real-time data generated at various sources across all phases of production — from raw glass to shipping. At the heart of this solution is the secure Industry 4.0 platform, which Enterprise Services has developed in collaboration with Fraunhofer IPA. It enables to combine data from both Information Technology (IT) as well as Operation Technology (OT) sources. In this case, the machine, sensor and other shop-floor data came from enterprise resource planning system, manufacturing execution system, business warehouse and calculation systems. When combined onto a real-time analytics platform, the real-time cycle of detect/analyse/act/respond and fix is constructed, thus creating a possibility for a self-healing process in any sub-segment of the lens production.

The impact of the real-time and actionable data analysis is immediate and dramatic: boosting factory capacity — by saving time — and using fewer materials, thereby reducing costs are immediate benefits. A valuable outcome of producing and shipping eye glasses more quickly is enhanced customer satisfaction, but another key impact of the efficiency drive is higher output:  what started out as an efficiency, quality and cost reduction ‘fix’ created a fresh revenue opportunity.

Kaeser discovers new business model in predictive maintenance 

Kaeser Kompressoren is a global manufacturer of compressed air systems in the heavy industry sector, selling and servicing hundreds of thousands air compressors to a large customer base around the world. Its products are known for outstanding reliability, energy efficiency, cost efficiency and ease of maintenance, all of which help Kaeser maintain maximum customer satisfaction.

With the majority of Kaeser’s products used in industrial processes, ensuring continuous availability is critical because unplanned outages adversely impact customer productivity. A large and diverse customer base, including global enterprises and SMBs, compounds the challenge of providing high quality maintenance services and support.

Collecting and analysing data to gain a true picture of faults occurring would provide competitive breakthrough. Together with DXC Technology, Kaeser piloted a real-time analysis of sensor data from installed compressors located on client sites. The Smart Connected Manufacturing and data analytics exercise created an automated, predictive maintenance cycle and achieved the desired result of higher uptimes.

But, as is often the case on Smart Connected Manufacturing journeys, the pilot also exceeded expectations in other ways. Based on uptime, plus improved reliability and predicted capacity, Kaeser reinvented its business model: as well as its traditional model of selling equipment and maintenance contracts and spare parts, it can now also sell compressed air by the hour as-a-service.

In the new, servitized business model, Kaeser now keeps ownership of costs, and all the risk. But business risk is massively reduced because the manufacturer has sight-of-repair of costs and failures through its digitally-enabled predictive maintenance cycle. Doing business with the new model means the manufacturing giant saves 10 million Euros in spare parts alone.

Car maker does ‘just-in-time’ personalization

A third case study, which I presented at Discover London, is of a global car maker using robotics to build cars to personal order — on the same assembly line. Robots programmed from the cloud enable the pioneering car manufacturer to respond to customers’ personal tastes and configure different vehicles on a single production line, without any reassembling. Not only can colour and fabric variations to the bare metal be customized, but also value added services relating to software and integration.

At the heart of all these stories is our secure Industry 4.0 platform, which DXC has developed in collaboration with world-renowned academic institute, Fraunhofer IPA. Essentially, the converged platform enables manufacturers to combine data from both Information Technology (IT) sources, such as the front and back offices, with Operation Technology (OT) sources on the factory floor.

It’s no surprise that the audience at Discover 2016 wanted to hear how they could embark on their own smart connected journey to Industry 4.0. The first step may sound boring — but it is essential! Understand your base line — the limitations and constraints of your current situation. The challenge is not to get a new piece of digital tech working, but how to introduce it in a secure and seamless way to existing operational and information technology infrastructures.

Where to start with your Smart Connected Manufacturing pilot

Picking a potential pilot to start is the next step for manufacturers wishing to get on a path towards Smart Connected Manufacturing. When you’re having to maintain a bigger picture it’s important to have an easy way into the journey.  This small step provides an initial purchase on the environment of Industry 4.0.  Choose a process or product or market segment where there’s a problem to fix, start with an early proof-of-concept that can be executed quickly and show results.

It’s also important to get a balance between top line priorities — revenue and growth on the one hand, and internal profit-oriented cost efficiency angles on the other. Both have to be balanced: growth versus cost and profitability. The instances of Kaeser and Zeiss respectively illustrate these two levers for transformation. Scoping a potential pilot against both of these objectives is a useful way to simplify the potential complexities of navigating an integrated world and converging technologies.