Is blockchain changing the way trust, transparency and revenue is viewed in manufacturing supply chains?

INDUSTRY REPORT

Blockchain and the manufacturing supply chain

Blockchain is changing the way trust, transparency and revenue in manufacturing supply chains are viewed, says Karthik Sundaram, program manager – industrial at Frost & Sullivan.

Blockchain is a digital ledger that purpose of a blockchain. If there are agreements) and shorter maintenance can be used to store, record defective products in a supply chain, times. blockchain can also support and manage transactions. they could be easily tracked across more complex machine-as-a-service Originally created to support entities in a way that has never been (MaaS) applications by facilitating financial transactions with the aid done before. Instead of shuffling IP protection, documentation of smart contracts, it can support through a bulk of papers, bills, management, and performance the transfer of any data or digital files, data and emails, a blockchaintracking. asset. As records along the chain are based system could track goods with But, is blockchain ready for factories? stored and distributed across different certainty throughout their journey. Yes, says Frost & Sullivan. It is confident nodes in the network, it is difficult Uniform, aggregated data will that blockchain will have a critical to counterfeit these records, making also allow manufacturers to perform role to play in shaping the future of blockchain a secure, immutable higher levels of predictive analytics. factories. Undoubtedly, it will bring and transparent way to record and One of the biggest challenges in greater efficiencies to the supply chain, service transactions. This advantage modern supply chains is the ability to better coordination in automation, and strengthens the cause for blockchain get all of the data in the right place, maximum transparency when dealing applications outside of cryptocurrency at the right time and within the same with counterfeit trade. However, it exchanges. framework. blockchain would help believes that the rising diversity of

Much of the potential for realise this scenario. It would allow applications and the complexities of blockchain in manufacturing has, to data to be used along with several manufacturing supply chains could date, remained theoretical. Globally, other technologies – such as artificial delay blockchain adoption. The factories manufacture products in huge intelligence – to maximise efficiencies. transformation will therefore require volumes. However, there is still no This data could also be sold, providing proactive collaboration among guaranteed method of knowing how, companies with an extra revenue manufacturers, policymakers, scientists when and from where these products stream. For example, blockchain and technology investors underpinned originate. In almost every case, the can support new maintenance by new platforms that can support this journey of a product to the end user approaches (such as automated service transformation. remains unseen, resulting in a lack of transparency, despite the fact that over 50% of customers today are seeking transparency in the production process.

If a manufacturing supply chain can be made transparent, everything could be monitored and made visible to all stakeholders. This will help manufacturers establish trust in the system and their products.

One of the key areas where blockchain can bring value is in the audit trail. Currently, there is no uniform standard to aggregate and share data. Modern supply chains need a system that can enforce standards for parties to access the full set of data they require. Essentially, this is the

INDUSTRY REPORT

Are we set for a surge in AI investment?

According to new findings of research undertaken by IFS, a global enterprise applications company, manufacturers are planning to aggressively invest in Artificial Intelligence (AI) technologies.

The international research, which examined the perception and adoption of AI within the sector, revealed that 91% are planning to invest in AI strategies. Industrial automation and inventory planning & logistics were cited as the key focus areas by 54% and 40% of respondents, as manufacturers seek to enhance productivity and boost efficiency.

IFS’s study polled 383 manufacturing decision makers working with technology including Enterprise Resource Planning (ERP), Enterprise Asset Management (EAM), and Field Service Management (FSM). The study revealed that manufacturers saw AI as a route to create, rather than cull, jobs. Around 51% of respondents stated they expect AI to increase headcount, while 22% believed it won’t impact workforce figures.

Alongside investment in AI to support industrial automation and planning & logistics, scheduling was also viewed as an area of opportunity for investment, with 36% planning to use it to enhance production scheduling and 25% for service scheduling. Only 6% intended to invest in AI for customer relationship management, differing significantly from other sectors which see this as a major use case.

“AI is no longer an emerging technology. It is being implemented to support business automation in the here and now,” said Bob De Caux, VP of AI and Robotic Process Automation (RPA) at IFS. “We are seeing many realworld examples where technology is augmenting existing decision-making processes by providing users with more timely, accurate and pertinent information. In today’s disruptive economy, the convergence of technologies such as AI, RPA, and IoT is bolstering a new form of business automation that will provide companies that are brave enough with the tools and services they need to be more competitive and outflank larger competitors.

“The findings of the study show that the time is right for manufacturers to reap both business and financial benefits from technology automation. Falling for the hype of AI is easy, but success requires disruption to existing business models. The technologies themselves are not a panacea, nor are they a universal solution to any problem. However, with the right data model and viable use cases, AI can support improved productivity and deliver significant benefits to both operations and the wider business. AI will be used by the vast majority of organisations in some form in the near future, extracting real value from intelligent processes, for the long-term.”

5G will require a new approach on the factory floor

By 2026 there will be 5.3 million 5G connections on the factory floor according to ABI Research.

As a technology, 5G will be a good fit to provide wireless connectivity on the factory floor, as it enables, for example, establishing a huge wireless sensor network or implementing Virtual Reality (VR) and Augmented Reality (AR) applications for predictive maintenance and product monitoring.

Early 5G trial deployment projects – at companies such as Schneider Electric, Osram and Mercedes – hint that bringing 5G connectivity to the factory floor will decrease maintenance costs by 30% and increase overall equipment efficiency by 7%.

While there are many use cases and areas of application for 5G in industrial manufacturing, targeting the enterprise vertical will fundamentally change the value chain associated with 5G. However, this will require closer collaboration between network operators, infrastructure vendors, and manufacturers.

A recent Return on Investment (ROI) study conducted by ABI Research has shown that 5G will take approximately 14 to 15 years to break even if it remains solely in the consumer market, versus 10 years if enterprise business models were in place. “It is, therefore, highly important for network operators and infrastructure vendors to develop new business strategies taking into manufacturers’ requirements,” said Leo Gergs, research analyst at ABI Research. “Centrally, this should include moving away from selling connectivity as such and develop attractive pricing models for additional network capabilities.”