HARNESSING DATA FOR REAL-TIME DC ASSET MONITORING Minimize downtime, improve performance, and transition to predictive maintenance

Harnessing Data for Real-time DC Asset Monitoring | Table of Contents i

TABLE OF CONTENTS

1 Introduction2 Making the Business Case for IIoT2 What downtime really costs

3 2019 growth: E-commerce vs. total retail sales

3 The hidden value of predictive maintenance

4 Transitioning to a More Connected Future5 Utilize What Your Control Systems Can Tell You5 Address performance issues with data

6 Expand your operational awareness

7 Predict (i.e., Stop Reacting to) Maintenance Needs8 Consult with experts to ensure program success

8 How to lead a digital transformation effectively

9 Summary

Harnessing Data for Real-time DC Asset Monitoring | Introduction 1

INTRODUCTION

Real-time asset monitoring programs — or the ability to connect machinery and automation systems via the industrial internet of things (IIoT) technologies — represent immense untapped potential for distribution and fulfillment (D&F) operations.

From the reduction in unplanned downtime to increased throughput to maximized facility utilization, effective implementation of these programs helps to significantly reduce e-commerce order fulfillment complexities. While the industry is still in the early stages of adoption, most companies in the D&F sector recognize the need to begin implementing IIoT programs.

The benefits of IIoT technologies (aka Industry 4.0) have been well documented in other industries for more than a decade. Connectivity of machine control systems, sensors and other devices networked with business and management systems allows for data collection, exchange and analysis — all of which can facilitate improvements in productivity and efficiency and deliver economic benefits. This white paper will discuss the need to disrupt manual methods of gathering and reporting daily operational data, and the importance of making a transition to capture continuous asset health and performance insights — and how to leverage this data to detect asset degradations, maximize uptime, and minimize operational costs.

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Harnessing Data for Real-time DC Asset Monitoring | Making the Business Case for IIoT 2

MAKING THE BUSINESS CASE FOR IIOT

Running efficient distribution center (DC) operations is a key to survival in the hypercompetitive e-commerce and omnichannel retail market. But while 90 percent of companies say their top priorities are durability, reliability and uptime, few have invested in a digital transformation of their material handling operations.

A 2010 U.S. Department of Energy (DOE) study of operations, maintenance and energy professionals revealed that the average savings from an IIoT-driven predictive maintenance operation delivered a 10:1 return on investment (ROI).

Performance improvements of this magnitude should appeal to DC operators and enterprise managers. Indeed, many companies recognize the need to fundamentally shift how they run D&F operations. In fact, 70 percent of material handling executives consider investments in Industry 4.0/IIoT technologies a top priority. Yet only 2 percent of executives identified supply chain performance as a focus of their digital strategies. In our industry, the importance of connected DC assets may be underestimated and/or their potential benefits difficult to measure.

Market leaders and early adopters have demonstrated that real-time asset monitoring — combined with data analytics capabilities and machine learning in warehouse automation software — can provide early detection of DC equipment failures and predict maintenance needs. The value of IIoT technologies is also well-known in other industrial sectors. For example, the oil and gas industry has embraced the power of operational data to improve process quality and grow their bottom lines. It’s time for D&F operations to realize similar transformative benefits.

WHAT DOWNTIME REALLY COSTSUp to 80 percent of businesses are unable to accurately estimate their downtime rates. Many underestimate downtime costs by 200–300 percent. The following factors are often ignored when calculating downtime:

• Depleted inventories

• Disruption to innovation

• Lost production

• Missed customer SLAs

• Recovery costs

• Stressed equipment and systems

• Wasted labor and productivity

• Weakened brand loyalty and customer trust

Harnessing Data for Real-time DC Asset Monitoring | Making the Business Case for IIoT 3

D&F operations face escalating order fulfillment complexities, not the least of which are the rapidly changing requirements driven by the growth and complexity of e-commerce orders. The lack of a strong business case, unfamiliarity with digital supply chain technologies and difficulties proving an ROI are often cited as key barriers to adopting IIoT programs in the D&F sector. Nevertheless, this lack of investment potentially raises opportunity, maintenance and other costs.

Based on current trends, investing in the capabilities to predict equipment failure and achieve visibility into operations will become even more important. Market growth in the next three to five years, along with a declining technician workforce, will dictate the need for more predictive automation. Costs associated with unplanned downtime will only escalate as the industry grows and automation systems become more advanced and widely utilized. Today, the cost of 30 minutes of unplanned downtime could easily cost 3–15% more in a year. As a result, DC and enterprise operators will need the insights to implement smarter processes and achieve more reliable equipment operation.

2019 GROWTH: E-COMMERCE VS. TOTAL RETAIL SALES

14.9 percent E-commerce

3.8 percent Total retail

THE HIDDEN VALUE OF PREDICTIVE MAINTENANCE IIoT-driven predictive maintenance operations enable energy companies to improve processes and reduce costs, according to key performance indicators (KPIs) studied by the DOE, such as:

25–30% reduction in maintenance costs

70–75% elimination of equipment breakdowns

35–40% decrease in downtime

20–25% increase in production

Harnessing Data for Real-time DC Asset Monitoring | Transitioning to a More Connected Future 4

2TRANSITIONING TO A MORE CONNECTED FUTURE

Surviving in the hypercompetitive D&F marketplace will require businesses to accelerate their digital transformation and adoption of IIoT programs.

Because this transition will disrupt the status quo of traditional maintenance and operations programs, the shift toward IIoT cannot be implemented without leadership across the organization who are aligned on a viable change management strategy. Without this, businesses often struggle to demonstrate the ROI in their progression toward becoming a data-driven enterprise.

Moreover, the risks of doing nothing may be greater in a world where reliable, consistent uptime is a true differentiator. Here’s an example: Skilled service technicians are vital to an operation’s success. But as a generation of service veterans nears retirement, fewer qualified technicians are available to replace them. According to some estimates, industry growth is outpacing the available labor pool by a ratio of six to one. This creates a significant knowledge and service gap that clearly is a present- and long-term threat to operations. As a result, DC and enterprise operators are in a never-ending race to improve training processes, recruit candidates, and quickly get them up to speed. By capturing valuable historical data from maintenance and operation of the system over its lifecycle, companies can accelerate new hire training and proficiency, benchmark performance, and even leverage this data to upskill their staff on a continual basis.

All these challenges present opportunities for real-time asset monitoring programs to succeed.

Harnessing Data for Real-time DC Asset Monitoring | Utilize What Your Control Systems Can Tell You 5

3UTILIZE WHAT YOUR CONTROL SYSTEMS CAN TELL YOU

Leading retailers are testing the IIoT waters via pilot programs. A good place to start is by tapping into the vast amounts of available data from machine control systems on existing assets.

It’s estimated that there are hundreds of thousands of data points that can be accessed from a control system, but this data is largely underutilized. Some operators pull data from programmable logic controllers (PLCs) periodically throughout a day or shift. Because PLCs are only capable of storing limited amounts of data, this information alone is transient and offers no trending information or insights. What’s more, it’s estimated only roughly 25 percent of this data has any real value.

To extract value from control system data, distribution and enterprise operators need software and analytics tools to make sense of it. By continually aggregating and interpreting this data, these tools filter out the noise to deliver historical trends and actionable insights that provide tremendous operational value. Analyses of conveyor run statuses can help operators evaluate KPIs such as conveyer jams, flow balance through merges, read rates and all-important throughput rates.

By connecting control system data to software with alarm management capabilities, operators can access real-time dashboards and receive email, text and mobile app notifications when key issues impact operations. These tools can help companies formalize issue escalation processes and uncover repetitive issues that can be potentially predicted — and even prevented.

ADDRESS PERFORMANCE ISSUES WITH DATA• Resolve conveyor faults that

create repetitive jams.

• Uncover scanner timing and read rate issues to prevent unnecessary recirculation and manual handling.

• Automatically log the duration of downtime in pick stations, merges, transfers and recirculation loops.

Harnessing Data for Real-time DC Asset Monitoring | Utilize What Your Control Systems Can Tell You 6

EXPAND YOUR OPERATIONAL AWARENESSTo provide deeper insights into system performance, including the ability to predict equipment and system failures before they occur, you’ll need to add condition sensors on equipment motors and gearboxes.

Data extracted from vibration and temperature sensors — combined with smart analytics software, machine-learning algorithms and artificial intelligence (AI) — can detect and track deviations from performance baselines. Today’s machine-learning algorithms generate alarms when parameters exceed defined temperature and vibration thresholds on any equipment utilizing motors and gearboxes.

In the case of sortation system gearboxes, here’s an example of insights that real-time monitoring can provide:

• Trending data from analytics software indicates an incremental, steady increase in gearbox vibration.

• The alarm management system sends a notification that corrective action is needed before the next scheduled preventative maintenance (PM) interval.

• Upon inspection, technicians perform a series of maintenance tasks:

- Confirm drive belt tension.

- Inspect and adjust end rollers.

- Ensure drive belt alignment.

• After servicing the gearbox, the analytics software indicated that vibration had returned to normal levels.

If maintenance teams waited until the next PM interval, there’s a high probability that the vibration could have escalated to equipment failure — shutting down the conveyor and causing a domino effect of performance issues and missed SLAs.

Trending data from analytics software

The alarm management system

The analytics software after servicing the gearbox

Harnessing Data for Real-time DC Asset Monitoring | Predict (i.e., Stop Reacting to) Maintenance Needs 7

4PREDICT (I.E., STOP REACTING TO) MAINTENANCE NEEDS

By connecting analytics insights to other fulfillment technologies and existing business systems, operators can automate the creation of service tasks and make the transition to a true predictive maintenance model.

Doing so requires integrating one or more of these key enabling technologies with a connected DC infrastructure:

• Computerized maintenance management system (CMMS)

• Voice-directed maintenance and inspection technology

• Augmented reality smart glasses for live troubleshooting

DC operators could potentially automate the entire find-and-fix process from issue detection to resolution:

• Analytics software detects when a KPI is out of range.

• Work order request is triggered to an on-site maintenance technician.

• Technician receives an alert, then initiates a voice-guided inspection workflow.

• Smart glasses allow the technician to share live audio/video with OEM experts.

• Technician completes voice-guided work, records the fix for future reference, and automatically generates a CMMS report/issue resolution status.

Once connected, deeper insights into real-time and historic equipment health are available from some predictive software applications. Armed with these tools, DC and enterprise operators can investigate symptoms and root causes of asset degradation. The advanced capabilities can be utilized to investigate a variety of issues that sap DC productivity, including:

• Current draw of a power control panel

• Forces from sustained impact from products on equipment

• Temperature and vibration of conveyor and sortation motors

• The time of an exception and its surrounding conditions

Harnessing Data for Real-time DC Asset Monitoring | Predict (i.e., Stop Reacting to) Maintenance Needs 8

HOW TO LEAD A DIGITAL TRANSFORMATION EFFECTIVELYMost IT decision makers (81 percent in 2019) have seen a digital transformation project fail, suffer a major delay, or get scaled back. The most common barriers to successful IIoT adoption are well-known and can be overcome when you take steps to make sure your organization:

• Understands the technology landscape and its effects on your business

• Deploys adequate talent to implement and utilize the technology effectively

• Justifies the investment

CONSULT WITH EXPERTS TO ENSURE PROGRAM SUCCESSWhen undertaking any IIoT program, many companies start with no clear understanding of program objectives and their impacts on the business. Often this uncertainty is combined with a shortfall of qualified internal staff needed to effectively implement programs and leverage the technology to its fullest. As a result, IIoT programs either fail or don’t produce the required results.

Thus, it’s critically important to partner with an IIoT provider who can 1) help your business establish clear, attainable business objectives and 2) ensure that your staff has all the support it needs to implement them. Typically, this means calculating the proposed return on investment so that there’s a clear correlation between the program’s objectives and the value generated.

It also means having access to a dedicated IIoT success team to help keep the program on track and even see it through to completion. This consultative partnership model supports a cycle of ongoing improvement and increasing IIoT utilization — building on the success of each successive program to justify the next investment — which could ultimately lead to full IIoT engagement for the lifecyle of the material handling system.

THREE STEPS TO SUCCEED

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• IIoT adoption leaders are 75 percent more likely than IIoT laggards to cite the preparation of a well-articulated vision for value creation as a key factor in their project’s success.

• Digital transformation is an iterative process.

• Choose a key operational area about which many stakeholders care and establish time-bound parameters.

• Create an actionable business plan with goals for achieving a specific financial outcome.

CREATE A STRONG BUSINESS CASE.

START SMALL AND CLEARLY DEFINE THE SCOPE.

BUILD A COMPETENT, CAPABLE IIOT INNOVATION TEAM.

• Visionary: establishes the overarching direction and a precise road map

• Motivator: engages the team with a common goal and coaches others along the way

• Executor: marshals the necessary resources to drive change through your organization

Harnessing Data for Real-time DC Asset Monitoring | Summary 9

SUMMARY

Forward-thinking companies are building real-time asset monitoring into their new DCs to enable predictive capabilities and protect their equipment investments. Existing D&F facilities have just as much to gain. They can be retrofitted with equipment sensors, smart analytics and visualization software.

Regardless of your business or operational goals, Honeywell Intelligrated has the technologies to enable you to create a more connected present and a more predictable future. Our Connected Assets offering helps customers enhance their operations immediately while laying the groundwork for ongoing, data-driven performance improvements.

With decades of experience providing industrial automation and analytics software for process control, Honeywell Intelligrated is uniquely positioned to deliver deep operational insights in the distribution and fulfillment sector. By combining the infrastructure of The Connected Distribution Center with these proven software tools, we help DC operators and enterprise managers implement effective predictive maintenance programs and uncover hidden utilization potential.

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