Uptime: When Best Practices Aren’t Enough

Consider the following remarks.

“Recently, our top executives announced that our cost of manufacturing still wasn’t what it needed to be, even with all the maintenance improvements and lean initiatives over the past few years. And while our quality and delivery continue to be topnotch, one of our largest customers served an ultimatum that they would be taking their business overseas unless we could improve our pricing.”

“Despite all the maintenance best practices we’ve deployed, we (and others) are finding the department under the cost-cutting knife again. We’ve improved our spare-parts management significantly in the past two years, including stock outs, inventory levels, critical spares, and obsolete parts. Our maintenance labor hours are 90% proactive. But, new equipment continues to be added to the mix to reduce operating labor costs. What should we do?”

Sound familiar?

The real goal

Cost cutting is not a goal. It’s an action deployed as a way to achieve a short-term business goal—one that’s often short lived.

Here’s the challenge: While executives may be preparing for another round of cost cutting, there could be a more powerful alternative. It’s going to take thinking outside the maintenance box, however, to look at manufacturing process reliability. The real goal here is to show management how it can reduce manufacturing costs and position the business for higher earnings growth by tapping into the plant’s hidden capacity.

I recently discussed this approach with a company’s top executives and plant-leadership team. They talked about how strong their business was this year and on into early next year. Their honest concerns centered around getting costs under control to improve the company’s earnings in light of the potential loss of a large customer looking for price cuts. They summarized their strategic performance indicators as three overarching goals:

• On time, in full—orders shipped to customers on time in the quantity and quality requested.
• Lead time—reduced time between order received and order shipped.
• Cost per unit produced—lowest all-in, total cost of making a product.

These executives were describing their goals for a reliable manufacturing process, i.e., a process that performs as intended. Their vision reflects a real opportunity for the organization—one that eclipses another cost-cutting initiative.

Tapping into a plant’s hidden capacity can help cut manufacturing costs and position the business for higher earnings.

Thinking beyond maintenance

Let’s explore this opportunity by thinking about reliable manufacturing processes, i.e., thinking beyond maintenance. The executives who spoke with me agreed to form an improvement team of hand-picked personnel, including the maintenance manager, production operator, maintenance mechanic/union president, front-line supervisor, manufacturing vice president, and the continuous-improvement/quality director. The team used the following data-mining process to get started:

• Identify the strategic key performance indicators (KPIs), i.e., lagging indicators.
• Mine company data to determine the leading indicators and what form they take.
• Determine how plant performance is inhibited, according to the current data.

The next step involved a review of top-level indicators that plant leadership was focused on improving, including:

• labor efficiency variance as a percentage of standard
• indirect factory labor as a percentage of revenue
• operating expense as a percentage of revenue
• obsolete materials and work in process (WIP).

Team members then began to look for specific factors that contributed to labor, operating expense, and materials cost. They also looked for factors that could interrupt flow through the entire manufacturing process to the paying customer.

Based on the team’s review of various ad hoc reports from the company, the improvement team found the most frequently listed reasons for the plant performance losses to be:

• ran out of work in process (WIP) to meet an order.
• ran out of raw materials to produce to plan.
• inaccurate inventory: WIP and raw materials.
• schedule change: materials delayed upstream.

The improvement team also learned that material cost was the highest cost of manufacturing and labor cost was the lowest.

Asking ‘why’

Drilling down another level into the most-frequently listed reasons for plant-performance losses was the improvement team’s next step: For example, answers to Why did we run out of WIP to meet an order? included:

• no reason
• system quantity was different than what actually existed
• some named items were defective and could not be used.
• items needed were on quality control hold.

Asking Why did we run out of raw materials to produce to plan at the upstream production processes? revealed some similarities:

• not enough materials on skid, wrong count.
• some materials were defective, damaged.

Team members soon recognized that they were discovering why production flow was being interrupted in the plant. In turn, they began wondering if equipment issues, i.e., breakdowns, might also be leading to performance losses. Digging into machine-downtime-tracking information, they found documentation that stated: Machine down for repairs, no operator, no reason listed.

To learn more about the nature of repairs in the plant’s critical-constraint production department, members of the improvement team began discussing machine downtime issues with personnel in the maintenance and operations groups. It was learned that the losses were not so much about equipment breakdowns, but rather:

• setup problems
• equipment damage
• adjustments.

By asking why, the improvement team discovered that machine problems interrupted flow and were possibly linked to inventory and quality issues that had a direct effect on plant performance and the top KPIs (key performance indicators). Unfortunately, other than through maintenance requests, very few machine-related losses were being reported, tracked, or systematically analyzed. This situation had to change if plant reliability was to improve.

Tracking major equipment losses

What equipment-related losses should be tracked to improve plant reliability? The improvement team identified the types of losses that would most likely have a strategic impact on the business: equipment-utilization losses. Here’s how team members agreed to formally collect and categorize equipment performance data for the 17 most critical assets in the plant:

Equipment capacity (designed or historical best)

• Planned capacity losses:

– Planned shutdown: not scheduled/no demand
– Planned shutdown: maintenance
– Planned downtime: not scheduled (breaks, shift change)
– Planned utilization: time that machine was scheduled to produce something

Utilization losses (during scheduled operating time, i.e., the hidden factory):

• Planned downtime: setup/changeover
• Unplanned downtime: no or defective WIP/material
• Unplanned downtime: breakdown
• Unplanned downtime: no operator
• Unplanned downtime: production schedule change and/or interruption
• Efficiency loss: slow-speed or throughput rate
• Efficiency loss: minor stops/startup/adjustment.

Yield loss: defects/damaged/scrap output

Yield loss: defects/rework

Yield loss: startup/adjustment

Actual asset utilization: the bottom line; what the equipment actually delivers).

The reliability mindset

In this case, the improvement team recognized that improving plant reliability is not as much about maintenance as it is about identifying and eliminating equipment-performance losses and interruptions to flow. And, to do that, it’s crucial to have equipment performance data that are accurate and timely.

The good news so far is that top-level executives and other plant leaders have agreed to identify and address the most significant equipment-utilization losses in the manufacturing-flow constraints. Stay tuned for more as this story unfolds.