What do managers in materials handling, warehousing and logistics need to know to ensure their systems are as efficient as they can be? How do they avoid drowning in a tidal wave of data? Ruari McCallion has been getting techy.

Welcome to Industry 4.0

Getting information is one thing; getting useful information is another. ‘Industry 4.0’, the phrase that seems to be everywhere, is founded on data. It is not just ‘smart factories’ that need and have to deal with data: warehouse management, logistics and materials handling are very much affected too.

The main goal of Industry 4.0 in supply chain management is to foster the intelligent networking of products and processes along the value chain. It means engaging the Internet of Things (IoT), other emerging technologies (such as blockchain) and advanced data enabled by AI (artificial intelligence).

With rapid advancements in analytics and machine learning (ML), companies have the power to actively examine transactional data in near real-time and use the insights derived to plug gaps and remedy revenue losses. With increasing complexity, materials handling functions cannot be handled using established planning and control practices.

Opportunities and challenges

Industry 4.0 technologies increase transparency, which means that performance across the entire value chain – including that of partners and suppliers – is becoming more visible. While decision-making will be more collaborative and efficient, machines are being enabled to make decisions and perform learning activities autonomously, based on man-made algorithms.

The technological organisation of logistics will change with the implementation of BI technologies, smartphone apps, AIDC and RFID technologies, and the miniaturisation of electronics.

A core task of ‘smart’ logistics and supply chain management is adding the right level of autonomy and intelligence to make it more efficient, effective, connected, agile and flexible. The right balance must be struck between semi-autonomous systems and human involvement, including ‘cobot’ working, automation and planning.

The booming availability of data is itself a challenge. From RFID to HMIs, through machine-mounted lubrication sensors, every little connector is either already equipped or capable of being equipped to provide data. How do we identify and discriminate between that which is vital, that which is important, that which is merely interesting and that which is clutter? How do we make best use of what really matters?

Time to start again?

At this point, you might expect a discussion of the investments that simply must be made, right away, to avoid your company’s obliteration. While it’s fair to acknowledge that some investment in systems will be needed, a lot of hardware is already in place – like the sensors, RFID systems and connectors mentioned above; as well as automated conveyors and AGVs (automated guided vehicles).

There is no need to rip everything out and start again. Those sensors and automatic aids are all collecting data on location, machine capacity and condition, availability and progress, on goods’ location, source and destination, and so on. But the average warehouse or logistics operation may not be capturing it. They may be asking why they would need to, when things are going along pretty fine right now as they are.

“Universal access to the internet, changing consumer preferences, new business models, and a wholesale reinvention of retail stores are changing the industry,” says Guy Courtin, GT Nexus Vice President, Industry Solution and Strategy, Retail. He points out that legacy warehouse management systems were built to handle the traditional linear movement of goods in the supply chain.

“They manage processes within the four walls of a warehouse, receive inventory, and facilitate its distribution to stores. Within that scope, most legacy systems get the job done.”