by Dickson Yeo, Senior Logistic Consultant, WDS Southeast Asia, Swisslog
Considering the advances in automated material handling technology that have occurred in recent years, it is a little surprising to learn that eight of 10 warehouses are still manually operated. But, with the fourth industrial revolution upon us — what is being called Industry 4.0 — that is changing.
The first industrial revolution was powered by mechanisation; the second by the assembly line and mass production techniques; and the third by computerisation, automation, and lean management. All three sparked major improvements in productivity.
Now, the convergence of connectivity, low cost sensors, big data and advanced robotics is creating the cyber-physical production systems that will be the hallmark of Industry 4.0. Industry 4.0 encompasses, but is also broader than the industrial Internet of Things (IoT). According to McKinsey and Company, five disruptors are driving the evolution to Industry 4.0:
1. The unending increase in data volume (big data)
2. Connectivity, especially low-power, wide area networks
3. The emergence of real-time analytics and business intelligence
4. New forms of human-machine interaction, such as touch interfaces and augmented reality
5. Improvements in transferring digital instructions to the physical world, such as in advanced robotics
Implications for material handling
As these disruptors advance, the intelligence of computers is being decentralised while more devices are equipped to connect and communicate, generating large volumes of data. In the warehouse, SKUs will connect with machines, and machines with other machines and with higher-level processes in enterprise resource planning (ERP) and warehouse management (WMS) systems. Distribution operations, outfitted with advanced networking and robotics, will respond to changing tasks and continuously reconfigure themselves — increasingly without need for human coworkers to intervene.
The reliability and cost of these technologies are now at a point that they fit into a business case to automate warehouse operations. A major component of that business case will centre on the industry’s dependence on labour — particularly seasonal labour.
Recently, a third-party logistics provider had initially planned to bring in approximately 800 additional workers to process orders for a number of retail brands during the last holiday season. The company, however, was able to hire only half that number, despite attractive bonuses and other incentives. That represents a serious threat to their business.
Competition for the limited labour pool has become intense and demographic trends are working against the industry. The pool of available workers is shrinking at the same time the pressure on wages from competition is growing. The industry cannot continue to throw labour to solve productivity challenges. The solution for many companies will be found in the smart, integrated warehouse systems of Industry 4.0. Connectivity and data analysis are important to Industry 4.0, but so too is advanced robotics.
Most are familiar with the large industrial robots installed behind security cages in manufacturing and recognise they lack the mobility, flexibility and dexterity required for multi-channel picking and packing. However, a new generation of lightweight, collaborative “cobots” has emerged capable of working alongside humans in the warehouse to alleviate the current labour challenge.
Building the foundation
The first step in the evolution to Industry 4.0 that material handling organisations must manage is developing the infrastructure to collect and convert big data into insights – smart data – that enable them to better predict demand, especially from unstructured information, such as that found on social media. These insights are what will enable an organisation to configure and adapt its equipment, cobots and labour to fulfill ever-changing and complex orders.
Four steps an organisation must take to develop this capability:
1. First, establish data science capabilities. With the intense competition for data scientists today, many organisations will find it difficult to build in-house capabilities; however, partnering with a data science consultant may prove to be an even better solution as you have immediate access to established supply chain experience. Partnering with a consultant can also provide more flexibility in dealing with peaks in demand for data analysis services associated with a warehouse redesign or quarterly reporting.
2. Simultaneously, build a data repository capable of aggregating business information from multiple sources, including ERP, WMS, web analytics and social signals. The rapid development of big data technologies provides a variety of “off-the-shelf” solutions that can be configured to your needs.
3. Audit devices within the warehouse to determine where you can collect IoT data to augment business data and develop a plan for enabling devices outside the network with the intelligence and connectivity required. The availability of low-cost sensors has significantly expanded the feasibility of the warehouse IoT.
4. Finally, ensure you can visualise your data in a way that delivers timely, actionable insights to internal stakeholders.
Once you master these initiatives, you then can begin using artificial intelligence to create feedback loops with prescriptive algorithms to adjust distribution processes on the fly based on demand or conditions within the distribution center. Calling this a vision of the warehouse of the future is perhaps understating what is happening. This is an intelligent and systematic makeover of distribution operations that will be occurring, in many cases, within the next 10 years.
Business leaders need to understand Industry 4.0 technologies and possibilities today — and begin planning how their companies will grow with them tomorrow. This is how innovative companies, such as Swisslog, actively work with forwardthinking organisations to help them develop the infrastructure and processes to support the evolution to Industry 4.0.
About the Author
Dickson Yeo has joined as the Senior Logistic Consultant of the Warehouse and Distribution Division of Swisslog since November 2016. He is providing specialist support in logistics operations, translating client’s requirement and processes into the automation designs and project realisations in Southeast Asia region. Prior to this, Dickson was a client and user of Swisslog solutions and systems for 12 years. He has implemented an Automated Storage & Caddy Pick Distribution Centre using Swisslog technologies in 2014; with a 52,000 pallets storage capacity and picking throughput of 120,000 cartons per day.