Changeover time is a term that refers to the period of time that passes between the release of the last piece of a product and the start of a new one, that is, it is the time that passes between model changes. This time is considered from the release of the last piece of a previous model until the first unit of the new product is released, which must meet the relevant specifications for the customer who requested it.
In the business and manufacturing field, when discussing how to improve efficiency, reduce costs and maximize productivity, it is inevitable to touch on the topic of mold or line changeover times. Imagine having a line or machine that is not working. You would have a resource that is, not generating income, due to a stoppage that can have multiple reasons. Now think that this stoppage is due to a reason considered inevitable, the changeover of the line. That is, the line or machine is being changed adapted or modified to produce a different product.
SMED Methodology for Changeover Time Reduction
As a concept, Changeover Time as well as the methodologies for its identification, calculation and reduction are attributed to the work of Shigeo Shingo (Japanese industrial engineer in the 1950s) who developed the SMED (Single-Minute Exchange of Die) methodology. This methodology is one of the most powerful ways to reduce line change time, since it allows you to reduce configuration time while increasing flexibility and efficiency.
Examples of Changeover Time and Its Impact in the Manufacturing Process
Now let’s talk about financial terms and implications of changeover time and its repercussions in terms of time and production costs. Let’s give a simple but powerful example that will help you understand the impact you may be having without even realizing it.
Let’s assume that you and your company have a changeover time of 30 minutes that occurs at least once every day on a specific machine or line, and a task is completed 5 out of 7 days a week. Considering 200 working days (lower limit of global working days), your company is losing a total of 100 hours in a single shift due to line change without producing.
Now, consider what a typical company in each industry produces during that time that you may have stopped producing:
| Industry Type | Product | Number of Products That Would Stop Production in 100 Hours | Average Cost of the Affectation (USD) |
|---|---|---|---|
| Automotive | Automobiles | 100 vehicles | $2,000,000 |
| Electronics | Smartphones | 50,000 phones | $500,000 |
| Food and Drinks | Water bottles (500 ml) | 200,000 bottles | $150,000 |
| Textile | T-shirts | 25,000 t-shirts | $75,000 |
| Construction | Cement blocks (unit) | 50,000 blocks | $60,000 |
| Pharmaceutical | Medications (tablets) | 500,000 tablets | $250,000 |
| Metalworking | Machinery parts | 5,000 pieces | $200,000 |
| Chemistry | Plastics (tons) | 50 tons | $100,000 |
| Energy (Renewable) | Solar panels | 1,000 panels | $300,000 |
| Aerospace | Airplane components | 10 units | $1,500,000 |
| Shopfloor (Manufacturing Industry) | Electronic components (PCBs) | 100,000 printed circuits | $400,000 |
| Rubber and Plastics | Tires (unit) | 25,000 tires | $300,000 |
| Packaging | Cardboard boxes (unit) | 150,000 cardboard boxes | $80,000 |
Note: These calculations are based on the standard times of each industry and the average cost of each item for a 100-hour stoppage valued at direct loss (visible effects), without considering secondary effects, such as loss of income, increase in production, maintenance costs, delays, to supply chain and penalties for non-compliance with customer demand.
Manufacturing Changeover Time Measurement Formula and Calculation
As you can imagine, the first step is to measure the rate or duration of your changeover time. To carry out this task, you will need to verify all the stop and start data of your daily production.
Although this task may seem simple, the accuracy of the data plays a fundamental role in the calculation. Therefore, it is often more complicated to obtain the data than to perform the calculation itself, as the vast majority of companies still use traditional methods and measurements for changeover time, such as pencil and paper, manual clocks at best, a stopwatch. However, the most competitive companies that seek to improve use electronic execution and recording systems for this.
Today, most companies are looking for mechanisms to be more competitive, including machine monitoring technologies supported by IIoT and both real-time monitoring systems and systems that automatically record information (Assets Management and Analytics). IIoT systems can provide accurate, automatic, real-time measurements of when each of the many machines on a production line is stopped, running, or getting ready. This gives you full visibility into your production pace and efficiency, improving in that way the OEE, helping you get better data, eliminate human error, and ensure information accuracy.
Calculation of Change Over Time
Once you have the changeover time data, whether obtained automatically (highly recommended) or manually, you should understand that this calculation, although it is simple, must comply with certain guidelines. The formula to calculate the changeover time is as follows:
- General Formula
Changeover Time = Total Machine Downtime during the Changeover
- Detailed Formula
If we break down the original Changeover Time formula into its two components, it would look like this:
Changeover Time = External Preparation Time + Internal Configuration Time
Where we understand that Changeover time is the total time that the machine is not producing, and it is related to a change (whether internal or external). Therefore, this total time is calculated by summing the time taken to perform external preparation tasks and internal configuration tasks.
Changeover time Practical Breakdown Example
Suppose you want to calculate the changeover time applicable to a food mixing machine in your food production line. In this process, you switch from a mechanism for foods that include chicken to one for pork or beef. To do this, you need to know the times for each task, which requires gathering the general data for external and internal preparations, as shown below:
External Preparation Time (38 minutes):
- Preparation of materials (transport to the consumption area): 7 minutes
- Preparation of tools (mixing blades): 6 minutes.
- Inventory review (proteins): 10 minutes.
- Preliminary adjustments on the machine (technical preparation of times): 15 minutes.
Internal Configuration Time (62 minutes):
- Tool change (removal and placement of blades): 10 minutes.
- Cutter cleaning (removal, disinfection, sanitizing): 27 minutes
- Final adjustments on the machine (calibration): 15 minutes.
- Initial quality tests (blade rotation test): 10 minutes.
In this case, the Changeover Time calculation would be:
Changeover Time = 38 minutes (Preparatory)+ 62 minutes (Internal Configuration)
=100 minutes
The Role of Smart Factory MOM as a Software to Reduce Changeover Times
The world is in a stage of competition due to the advent of Industry 4.0. This stage of the industrial revolution forces every company to seek better and more efficient manufacturing methods to stay competitive. For this reason, technologies such as Manufacturing Execution Systems (MES) and Manufacturing Operations Management (MOM) software play a key role, driving and leading efforts to reduce changeover times for an improved OEE on the production.
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Explore 10 best practices to control or reduce your changeover time in manufacturing.
Smart Factory MOM and MES systems leverage digital technologies like the Internet of Things (IoT), as well as traditional methodologies (adapted with modern methods) such as data analysis (through dashboards and self-calculated panels) and process automation.
Some of the advantages of a MOM software like Smart Factory are mentioned below:
Real-Time Monitoring (IIoT Systems)
Through the use of information technologies like machine communication, sensors, and IIoT devices, MES and MOM systems collect real-time data about the condition of machines and processes with continuous monitoring, to highlight potential issues, trigger early warnings to minimize unexpected downtime, and identify OEE improvement opportunities.
Scheduling Optimization (APS Systems)
Advanced Production Scheduling (APS) systems, integrated with MOM software, utilize sophisticated algorithms to optimize production planning.
Digital Instructions (e-SOPs)
Digitalized work instructions or digital Operation Method Sheets are vital for task execution. This reduces training time, minimizes errors associated with outdated or misunderstood instructions, and allows operators to execute changeover tasks without extensive training, with clear, visual, and data-capturing instructions.
Simulation and Predictive Analysis (Dashboards and Andon Boards)
Advanced manufacturing software like Smart Factory MOM offers simulation models that test different production scenarios to identify the most efficient configurations.
Improved Communication and Collaboration (Data Sharing and Notifications)
Integrating functions like production, planning, inventory, and logistics into a single manufacturing software (MOM or MES) facilitates coordination across departments.
Automated Inventory Management (Materials and Tools)
Integrated MOM-ERP or MES-ERP systems offer automated inventory management, ensuring tools, raw materials, and consumables are available on time without manual intervention.
Conclusion
Efficient transition time management is essential to reduce downtime, increase flexibility and enhance overall efficiency in operations.
By using smart factory technologies such as MES, MOM and IIoT, producers can improve transformation processes through real-time data insights, predictive scheduling and automation. These instruments not only reduce manual actions but also offer actionable information to standardize and improve the transformation process.
Finally, as reducing transition time directly helps increase OEE, this can improve the presence and performance of machines while preserving quality levels. A smart factory strategy transforms the transition period of a bottleneck into an opportunity to boost productivity and speed by meeting various customer demands more effectively and simply than a classic method would.
Contact us today and witness firsthand how our advanced scheduling capabilities can transform your manufacturing processes.
