Capacity Planning Graphic
Capacity planning is measuring the maximum amount of work a shop is capable of completing during a given time period.
By Nick Stanziola, senior consultant
Harbour Results, Inc.

It’s no secret that the mold building industry is busy. During 2017 and early 2018, many shops experienced rushed or missed delivery dates. In fact, according to Harbour Results’ Manufacturing Pulse Survey conducted in February 2018, respondents indicated that their utilization rate, on average, is 81 percent and is predicted by the end of the year to reach an average of 85 percent.

However, looking more closely at the workflow of a tool, more often than not, there are periods of idleness where no work is being done in the plant. To ensure shops are able to capitalize on this boom in the industry and maximize their efficiency, it is important to understand and manage capacity.

Is the facility’s throughput known? Can the bottlenecks be identified? What are the machines’ utilization rates? These are all questions shop leadership should be able to answer at any given time.

Capacity planning beats gut feeling

At its core, capacity planning is measuring the maximum amount of work a shop is capable of completing during a given time period. It requires shops to have an understanding of how long a job is going to take, what the bottlenecks are within a facility and the status of current jobs. It’s also important to look at booked jobs as well as those that have a high probability of landing in the near future.

All key resource groups in the shop’s value stream must be part of capacity planning. Typical focus areas are design/detailing, machining, polishing and tool assembly. First, shops must understand how long their machines run on a given project, as well as the workflow. Next, look at people capacity. How many designers and toolmakers (assembly and prove out) are working in the shop? What is their available time? How long will each job take in each area?

The more data collected and utilized in a feedback loop, the better a shop will be at estimating the work time for a given project. Reviewing each job at completion and trending performance to budgeted hours will help operations drive continuous improvement and competitiveness.

Once the data have been collected, it begins to be a function of layering each job time estimate into a schedule or a timeline.

Layer 1: Total available resources over a given time, including machine and employee hours. Don’t forget to include vacation time.
Layer 2: Hours estimate for each booked project.
Layer 3: Hours estimate for highly probable projects.

This provides a snapshot of a shop’s capacity and allows for better planning. It will identify pockets of available time as well as potential issues where there are not enough resources to finish a job on time. To be clear, capacity planning is not production scheduling. These are two related activities that shops must do, but the methods or processes to perform them can be mutually exclusive.

The best shops have tied capacity planning into their sales organizations to provide a clear understanding of when the shop has open capacity so jobs can be found to fill the gaps. The more lead time the sales team has, the better it will be able to identify and pursue the right jobs – whether those are outsourced machining or a bigger project. This provides the sales team an opportunity to utilize a more strategic sales planning process and be less reactionary.

Why is capacity planning important?

Although it can seem like a challenging task, developing and using a capacity plan is an essential tool that gives visibility and allows the shop to be optimized.

Still not convinced? What follows is a rundown of the benefits of capacity planning.

  • By understanding the time predicted to complete a job, the shop can be better managed to help ensure delivery dates are not missed.
  • It allows mitigation of margin erosion through better management of outsourcing by predicting and filling the gaps and accounting for rework or additional cuts.
  • Capacity planning predicts when the facility has gaps and space for work, which empowers the sales team to fill them.
  • It improves profitability because the facility is working at achieving a capacity goal and not just stretching jobs to fill gaps.
  • Planning allows the shop management to better determine when it’s time to invest in equipment or hire additional resources.

Measuring overall equipment efficiency drives better decision making

For mold shops, machining is a key leverage point. Improving throughput and quality provides benefits throughout the shop floor. More and more shops are focused on measuring uptime of a machine, which is good, but does not provide the information critical to optimize a shop. Those that are best in class are using the Overall Equipment Efficiency (OEE) measurement process. This is a combination of measuring three components: utilization, efficiency and first-time through quality.

To effectively look at all three of these categories, it is important that shops consider utilizing a machine monitoring software. Today, a number of monitoring options exist that shops can consider to more effectively measure machining. Initially, machine monitoring software only measured utilization or machine uptime in a variety of ways, but systems have evolved and now are able to capture efficiency at some level.

Following are a few approaches that leverage machine monitoring systems to determine machine efficiency. Although all of these have challenges, the information they provide will be helpful to shop leadership.

  • Feed rate override monitoring: In theory, each cutting tool has an optimal set of parameters for best performance. If the CAM programmers / programs utilize these standards consistently, then any setting other than 100 percent on the manual feed override controls is considered “non-standard.” Machine monitoring systems have created alerts and visual indicators when non-standard situations occur so they can be addressed in real time.
  • Project estimates: All CAM systems project estimated run times; however, real times will vary for each individual machine, depending on controller processing speed. Additionally, virtual machine simulation can provide runtime estimates more accurately. Either of these estimates can be used as a baseline to compare actual runtime to calculate efficiency.
  • Material removal rate (MRR): MRR calculates the amount of material removed over a given time. This can be used as a speed measurement for roughing and semi-finishing programs. However, it is important to note that varying surface finish requirements can make this method misleading for finish programs.

The final and most difficult to measure aspect of OEE is quality. Currently, most machine monitoring systems are not focused on product quality, so quality issues frequently are not captured until further down the mold building process.

Starting to capture quality performance before a block is taken off a machine is an important first step. Shops can use inspection checklist reports or scan the machined component and compare it to CAD data using a portable cloud scanner or machine touch probe.

Gathering all the data is important. However, it is more important that the data are analyzed on a regular basis and trends are identified. Unlike the production version of OEE, it isn’t necessary to multiply each of the OEE elements together to arrive at a single value or percentage. Rather, each element’s top issues should be addressed to drive throughput. Harbour Results recommends leveraging pareto analysis to look at the root cause of problems. This type of analysis will indicate if the shop is doing better or worse; identify bottlenecks or throughput issues; and point out other occurrences that impact a shop’s performance.

As a shop begins to gather data across various jobs, time estimates can be built for each machine on various types of projects. This history will provide part of the information needed to build a capacity plan. By tracking reality, shops will be able to develop a more precise capacity plan and maximize their performance.

As a senior consultant with Harbour Results, Inc., Stanziola implements operations improvement initiatives, turnaround, strategy execution, competitive benchmarking, product launch and program management processes for metal and plastics product manufacturers, stamping die and injection moldmakers. He has 20 years of experience in the industry, holds a degree in mechanical engineering from the University of Michigan, is a Six Sigma Black Belt and also is a Certified Supply Chain Professional (CSCP). For more information, visit www.harbourresults.com.


Machine Monitoring Considerations

When investigating different machine monitoring tools, it is important to identify the information and reports that will benefit the business most, as well as key features that will be required to effectively use the data. A few areas to consider include the following:

  • Reliability of data coming from the machine
  • Ease of connectivity – especially to older machines and controllers
  • Pareto reports (i.e. downtime reasons)
  • Trending reports by various time frames (shift, day, week, month)
  • Real-time reporting
  • Report flexibility
  • Ability to export data to a spreadsheet to run shop-specific analysis

As technology evolves, machine monitoring systems are analyzing machining in a number of ways, such as:

  • Job traceability of each block through each machine as it flows through the value stream
  • Traceability by programmer to understand offline vs. at-machine programming output
  • The type of program (rough, semi, finish, 2D) run by machine
  • Benchmarking across the industry by machine type/use