supply chain

By Daniel Theobald, CIO and co-founder of Vecna Robotics

Mobile automation was once considered a high-risk investment due to high costs, intrusive implementation processes, and few success stories. This article shows why autonomous solutions are now a more affordable, smarter, and better investment than ever before. This is part three of a four-part series focused on robotic integration in the material handling value stream.

For more than a decade, the choice between a manual vehicle (pallet truck, forklift) and an AGV (automated guided vehicle) came down to a simple ROI (return on investment) formula.

The cost to purchase and operate a truck (operator sourcing, salaries, training, insurance, and so on) was less expensive than purchasing a self-driving vehicle.

However, rising wages, safety costs, and an unprecedented labor shortage are rapidly reducing the effectiveness and practicality of manual equipment.

New sensor technologies, faster computing, good wireless networks, and smarter algorithms –including machine learning – have allowed self-driving vehicle technology to progress to the point where it is often the less risky option.

More importantly, it can unlock the full productivity of existing staff allowing businesses to be more competitive in the global marketplace which is being driven primarily by ever-increasing customer expectations.

Short-term benefits: the agility and safety of autonomous vehicles

The rapid growth of the e-commerce markets warrants 452,000 more material workers this year, and the logistics industry is struggling to find them. The lack of human labor is slowing down production and threatening the livelihood of many organizations.

KPMG’s 2018 Global Manufacturing Output found that two-thirds of CEOs believe agility is “the new currency of business; if we’re too slow, we [companies] will be bankrupt.”

Robots help the organization stay competitive and meet production goals despite the lack of labor. They increase the speed and production by working multiple shifts without overtime or decreasing quality of output.

Geodis, a global logistics company, increased productivity with over 50 percent less staff then forecasted after integrating autonomous vehicles into their operations. Additionally, XPO Logistics increased units picked per hour by almost 300 percent after adding robots to picking lines.

Furthermore, Material Handling & Logistics US Roadmap 2.0 found logistic robots reduced Gap’s concept to store time by two months and brought Zara’s down to 25 days.

These benefits trickle down to the customer through faster delivery and lower prices. Autonomous solutions help organizations remain agile and competitive in a world of rapidly changing expectations and shrinking labor pools.

Agility is important to the bottom line, but so is material handling safety. OSHA estimates 97,000 serious forklift-related injuries a year costing on average $129,336 per person per non-fatal incident.

Accidents involving material handling equipment are significantly reduced or even eliminated entirely when that equipment is automated. Automation also reduces accidents by freeing people from dangerous activities that often lead to musculoskeletal disorders (MSD).

MSD is caused by repetitive motions, insufficient recovery time between movements, and constrained body positions, common aspects of material handling roles.

SHARP Research Group reported MSD accounted for 21 percent of all state-funded disability claims between 2009-2013, 55 percent of which derived from lifting.

If robots take over the dangerous portions of material handling, they will help prevent MDS among employees and save the industry up to $12.5 billion a year.

Another often overlooked benefit of automated equipment is that it lasts substantially longer than manually operated equipment.

The computers that control the equipment consistently observe acceleration and speed limits, avoiding unnecessary heavy breaking, and are less likely to come into inappropriate contact with infrastructure and product, saving costs in maintenance and repair as well as product breakage or damage claims.

Long-term benefits: The power of transparency and predictive analytics

Autonomous vehicles provide substantial short-term financial benefits, but they also provide significant long-term value through information sharing and predictive analytics. Robots’ activities are tracked in real-time.

This information can be shared across entire fleets, legacy equipment, software systems, and human analysts. It creates a dynamic map of the value stream, allowing team members to continuously monitor processes, identify waste, make immediate improvements, and prevent future challenges.

A recent PwC study reported Bosch’s automotive supply chain transparency strategy could save the company approximately €1 billion while creating revenues streams of equal value by 2020. That same survey stated companies who adopt mobile robots and their associated systems would see a 15 percent increase in revenue over the next five years.

Automation solutions also support predictive maintenance technology. Software associated with autonomous solutions monitor the use of equipment to proactively determine the probabilities of future malfunctions, breakdowns, and maintenance activity.

PwC Global Digital Operations Study reported that GE invested in predictive maintenance and saved $200 million by reducing cycle times and repair resources. Data sharing and analysis help companies identify areas to make and save money, driving long-term financial success.

Lowering the risks: the power of mapping, simulation, and learning

A 2017 MHI survey reported 73 percent of respondent’s stated risk of obsolescence as a reason not to move forward with automation. With consumer expectations rapidly changing and technology rapidly advancing, operations cannot justify financing purchases that quickly become outdated.

However, automation solutions with the ability to learn and adapt can help address this fear.

For instance, Vecna robots learn as they work, constantly acquiring new skills and sharing that information with other robots at the facility.

When a robot encounters a challenge, it sends an alert to Vecna’s Beacon service. This service analyzes the information and feeds it back into the organizations entire fleet in real-time.

The next time this situation occurs the entire fleet knows the most efficient way to handle the situation.

This process not only strengthens the capabilities of the robot but also removes a piece of waste from the incident value stream map (Figure 1).

Typically, an employee needs to alert a solutions provider of an issue before they can fix it.

However, Vecna’s solutions often solve the problem before there is any substantial negative impact; saving the organization time, money, and manpower. This service creates a constant cycle of improvement, nullifying the risk of obsolescence.

Obsolescence is just one risk associated with mobile automation; another major gamble is production downtime.

A report by enterprise strategy group found one hour of downtime costs industrial manufacturers between $30,000 and $50,000.

Adding mobile automation previously required extensive facility redesigns, widespread system updates, new hardware, and extensive testing to determine the best routes and uses. These changes led to months of downtime, costing companies millions of dollars.

Today, mobile automation providers offer infrastructure-free solutions that integrate into facilities without disrupting production.

Recently, Vecna Robotics deployed over 20 automated vehicles within a major shipping distributer in a month with zero downtime due to pre-deployment mapping and simulation services.

Mapping allows for quick and easy setup and route guidance – no additional infrastructure or construction is required.

Simulations determine how self-driving vehicles work best within the organizations’ existing layout. Simulations use data to assess the exact factors, processes, and results impacted or affected by mobile automation.

They evaluate multiple scenarios that align with specific organizational goals, consider the limitations of the operations, and reveal additional opportunities or challenges that may influence results.

Vecna Robotics recently deployed into a major third-party logistics – 3PL – companies and created 48 distinct virtual configurations to find the most efficient use, workflow, and type of mobile robot for their operation. The simulations predicted a 75 percent reduction in cycle time using a Vecna Tugger.

The actual reduction after deployment was one-point shy of this prediction at 74 percent. Infrastructure-free solutions using mapping and simulation technology ensure vehicles are optimally working from the moment they are installed, only increasing never decreasing production.

Competitive advantage in the next Industrial Revolution

The ROI for autonomous solutions has changed. Decreased purchase prices, lower installation costs, and minimised risks paired with growing short/long-term benefits prove mobile robots are a smart and essential investment.

Those who invest early in these technologies will have a competitive advantage moving into the next Industrial Revolution.

The agility, productivity, transparency, and predictive analytics these technologies fuel give those investing in them today a significant advantage tomorrow.

About the author: Daniel Theobald co-founded Vecna Technologies in 1998, with the mission of empowering humanity through transformative technologies. He’s been at the forefront of robotics R&D for over 20 years, partnering with DARPA, DoD, NASA, NIH, USDA and many others.

Today, he is the Chief Innovation Officer of Vecna Robotics. Vecna Robotics supplies Automated Material Handling, Hybrid Fulfillment, and Workflow Optimization solutions featuring mobile robots powered by a unique learning autonomy stack and the world’s first orchestration engine, Pivot.al.

Theobald is co-founder and President of MassRobotics and holds a bachelor’s and master’s degree in Mechanical Engineering from MIT. He has received the Henry Ford II Scholar Award, NSF Fellowships, and a Hertz Fellowship award.