The Industrial Internet of Things (IIoT) is transforming how manufacturing companies measure and improve processes. By using a machine data platform, companies can rapidly realize fast ROI and unprecedented improvements in efficiency and productivity.
But industrial IoT and machine data platforms alone aren’t magic wands that can be waved to create new value. While they do empower accelerated process improvement across an enterprise, they still need established measurement metrics and KPIs to provide context to the insights a machine data platform generates.
Measurements like takt time can give meaning to what the data shows, driving analytics and insights. Managers can view performance and implement changes where needed.
Takt time is the rate at which production must operate to meet customer demand.
When customers order products, they’re given lead times regarding when they can expect their goods. Takt time is used to measure a manufacturer's output against demand.
But it’s more than just increasing machine speed. A complex manufacturing operation requires multiple orders and order quantities from many customers. Companies within the same industry will have different takt times based on equipment age, minimum production lot sizes, and other factors. Looking at takt time individually and holistically provides valuable information to management.
If takt time is shortened, the operation is more efficient and has the capacity for new orders. If it exceeds what is needed to meet the lead time, processes are less efficient and customer dissatisfaction is high. Because of this, takt time helps measure the efficiency of a manufacturing operation.
Don't get confused with lead time and cycle time! What’s the difference between Takt Time, Cycle Time, and Lead Time?
The calculation of takt time is straightforward: the number of workable production hours divided by the number of units in manufacturing orders. Workable hours within the calculation shouldn’t include breaks, lunches, and other stops.
Takt Time (TT) = Workable Production Hours (PW) / Units Required by Customer (UR)
The traditional measurement of takt time relied upon manual data tracking, calculation, and analysis. Today, machine data platforms that record data in real-time can automatically calculate takt time.
This real-time access to takt time means managers can identify and respond to bottlenecks quickly. As production needs, inventory levels, and supply chain issues come into play, a machine data platform will deliver insights based on a data-driven, accurate takt time. Managers can understand what is happening on the production or shop floor and what needs to be done.
Because takt time is the speed production must run to meet demand, it’s only reduced by optimizing processes. Continuous improvement initiatives can help align takt time with demand; as processes improve, the cycle time of each product becomes more aligned with the required speed.
There are several ways to optimize processes and reduce takt time:
Cycle time is the time spent producing a good from raw material to the final product. Most manufacturing companies have many different products in their portfolio. The blend of other products ordered by customers is the "product mix" in production at any given time.
By measuring the cycle times and understanding their complexity, companies can plan resources for periods where takt time may be greater or lesser than desired. This measurement helps them make decisions in scheduling and planning to balance out takt time.
MachineMetrics automatically captures cycle times to ensure data accuracy and effective benchmarks. This allows managers to better understand and manage their take time.
Other process metrics to consider include:
A core principle of Lean and Six Sigma Methodologies is removing non-value-added time or waste. As improvement teams study and measure a product's cycle times and other performance attributes, they can divide activities and tasks into value-added and non-value-added time.
By eliminating the non-value-added time from process steps and formalizing it in the part's workflow, cycle time per product is lower. This leads to reduced takt time for the day, week, or other period being observed.
OEE is another way to review and improve processes. OEE considers availability, performance, and quality, and many companies assume their OEE is much higher than it is. By looking at the causes of downtime, companies can increase their OEE, and in turn, decrease their takt time.
Tracking historical OEE performance with MachineMetrics allows users to drill in at the machine, operator, or shop floor level.
Once a team has assessed production, taken performance benchmarks, and identified the root causes of problems, they can implement strategies to improve processes. The best way to do this is by using real-time machine data.
Improvement methodologies like Lean and Six Sigma began before the age of industrial IoT. But with advanced machine data platforms like MachineMetrics, processes can be taken to the next level with greater data accuracy and more actionable data.
Here are a few ways MachineMetrics can help you to reduce takt time:
Real-time data and advanced analytical insights drive process improvement, inventory optimization, waste reduction, OEE, and quality management strategies. These improvements mean that takt time can be reduced so that companies realize a competitive advantage.
MachineMetrics creates significant value that enables sales and marketing teams to reduce lead time for delivery. This reduction increases customer satisfaction and improves brand recognition.
Takt time is a valuable core metric for manufacturing production. Ensuring you have the accurate data necessary to track and reduce takt time is increasingly important given growing market competition.
Can we show you how we do it? Schedule some time with our team today:
47 Pleasant St, Suite 2-S, Northampton, MA 01060