With a background in computational biology, Rueben Scriven joined Interact Analysis two years ago and leads the warehouse automation and on-highway commercial vehicle research areas. Rueben has spoken at some of the leading industry events and moderated several panel discussions on the topic of commercial vehicle electrification. He’s also appeared on CNBC to provide insight on the global electric bus market.
Over the past 10 years, the way in which we order things and interact with retailers has changed significantly, and so too have the logistical operations required to fulfil orders. Historically, throughput tended to be the limiting constraint within warehouses, which gave rise to the ‘convey and sort’ style warehouse automation solution. However, as retailers continue to adopt and roll out omni-channel distribution models, new logistical constraints are becoming more prevalent – such as the need for system flexibility.
This insight discusses some of the biggest trends in warehouse automation solution design and the impact this will have on industrial automation vendors.
One of the biggest challenges e-retailers face is forecasting demand. It can be difficult for e-retailers to forecast sales a week in advance, let alone several years down the line. This poses a big challenge for when deciding how best to fulfil eCommerce orders. If the e-retailer opts for an in-house fulfilment operation using automation, the solution design will have to take into account future capacity requirements. Because this is often exceedingly difficult to predict, many e-retailers either under-utilize the warehouse asset during the first few years of operation, or outsource the fulfilment operation all together.
In order to address under-utilization, several warehouse automation vendors now provide modular solutions which can be scaled up or down depending on demand. Interroll, for example, has developed its Modular Conveyer Platform (MCP) which enables its customers to ‘re-wire’ the conveyor network using standard plug-and-play modules. This may result in changes in purchasing patterns as warehouse automation equipment providers may purchase components, such as drives and rollers, in higher volumes to build the modules in advance.
Flexibility Through Decentralization
Decentralization of the motor drive has been a trend that has experienced ebbs and flows over the past decade. In the past (and still today, to some degree) the trend of decentralization was driven by the amount of computing power that could be housed on a drive. Generally speaking, the more computing power a decentralized drive could hold, the more likely decentralized solutions were to be favoured over their cabinet mounted counterparts. Today however, there is a stronger driver of decentralized architectures which has enabled a certain staying power that had not been present in the past. That driver is the previously mentioned need for increased modularity within systems.
Decentralized drives had the highest year over year growth rates in 2019 when compared to other drive types. According to our analysis of the low voltage AC motor drives market, the decentralized drive product class grew nearly 12.1% in 2019; significantly fuelled by sales into material handling applications of which warehouse automation is a part. We take this to be a signpost for the prevalence of decentralized control systems more broadly.
Decentralized drives and to a smaller extent, motor mounted drives, enable enhanced flexibility and modularity within material handling systems. Since the drive is mounted in close proximity to the motor it is controlling, re-arranging conveyor systems to support times of reduced or increased demand is much more feasible. Additionally, decentralized drives are better suited to support plug-and-play modules than cabinet mounted drives due to the lack of prohibitively long cabling requirements.
The concept of modularity extends beyond conveyors. Adore Me, a US-based lingerie retailer, installed a highly modular, plug-and-play solution in New Jersey in 2018 integrated by Bastian Solutions. The solution used an AutoStore system connected to an Opex Sure Sort, both of which are essentially off-the-shelf products. When an order is placed, the items, which are stored in the AutoStore system, are brought to a picker standing on the periphery of the system. The items are then transported to an Opex Sure Sort which sorts and consolidates the orders. With the trend towards modular, plug-and-play solutions, the types of warehouse automation equipment being used will likely become more commoditized.
Warehouse automation vendors and system integrators will still provide retailers with ‘solutions’ but much of the customisation and design will be found in the software being used, as opposed to the hardware. In order to avoid becoming commodity providers, warehouse automation vendors and system integrators are expanding their software and service capabilities.
Predictive analytics is being adopted at an increasing rate across many sectors, and warehouse automation is no exception to that. Currently the most common application for predictive analytics has been maintenance. Within the warehouse automation sector, we’ve observed companies employing predictive maintenance features on their machines in favour of supporting novel business models. One prime example of this is Pearson Packaging’s machine as a service offering for its palletizers. This offering prices the machine based on its output as opposed to charging for the entire machine upon purchase. A model like this has an inherent need to keep machine downtime as low as possible since revenue is directly tied to the machine’s output. As a result, Pearson has employed machine level sensors and predictive analytics to determine when the machine is at risk of failure.
Pearson is not alone in this. Warehouse automation giant, Honeywell Intelligrated, offers predictive analytics through its Connected Assets program. Under this offering, motor equipment is monitored over time using vibration and temperature sensors to ensure unplanned downtime is avoided. Since throughput is such an important consideration for end-users of warehouse automation technology, predictive analytics is becoming more of a necessity. If the logistical nightmare of unplanned downtime during peak demand times can be avoided, end-users will be willing to invest. As the technology around predictive analytics continues to improve, we expect warehouse automation vendors to be amongst its early adopters.
Mobile Robots Displacing Conveyors
Ten years ago, the number of conveyors installed within a warehouse was often used as a proxy for its level of automation. Companies would strive for the title of having the most conveyors installed. However, the demand for shorter delivery times forced retailers to move their warehousing operations closer to urban areas where commercial real estate is significantly more expensive. Consequently, there’s been a greater demand for more space efficient automated solutions.
While conveyor systems are still the most common automation technology used for the transport of goods from one location to another, there’s a growing trend to use mobile robots for transportation. With a higher degree of flexibility, mobile robots are a plug-and-play solution requiring a smaller warehousing footprint than traditional conveyor systems. Furthermore, with the Robots-as-a-Service (RaaS) business model gaining popularity among smaller warehouses and 3PLs; SME’s and hub warehouses won’t have to make significant investments to automate their warehousing operations. Whilst we are forecasting positive growth for conveyors used within warehouses over the next five years, the growth rate is below that of the overall warehouse automation market.
Over the next five years, we’re going to see significant change in the warehouse automation market from new technologies to new business models. Within our Future of Warehouse Automation – 2020 study, we will be providing extensive insight and analysis on all of the trends discussed in this insight. Click here to speak to the lead analyst.