In the world of manufacturing, defective products are found every now and then. For any manufacturer, finding product defects can be irritating, as it means that these products will have to be disposed of or reworked.
Yet, wouldn’t it be great if there’s a method to prevent product defects? What if there’s a method where a task is always performed correctly and done right the first time? And that a product will always be manufactured perfectly, without any defect?
Introducing: The First Time Right method. Yet, what is the First Time Right method? What does it mean “to do it right for the first time?” And how does this method work?
In this article, we will introduce you to the First Time Right method, its technical aspects, some examples, and the tools you’ll need to have a defect-free production process.
At the end of this article, you can find a freely downloadable lean manufacturing e-book PDF and a quality management system e-book PDF, to help you achieve a total quality management oversight in your production facility.
What Is First Time Right?
First Time Right is a defect management method. In this method, every single step of the production process of an item must be done correctly from the very first attempt. If there are no errors in that item’s production process, then theoretically, that product will always be defect-free.
Getting everything right the first time is also a major efficiency advantage. As your assembly line doesn’t have to spend extra time and resources to re-work a defective product.
First Time Right’s Formulas
The First Time Right (FTR) method can be mathematically quantified. There are two formulas: the FTR Final Product Rate and the FTR per Production Phase Rate. Here’s how to calculate both:
FTR Final Product Rate
The most basic FTR formula is the FTR Final Product Rate. It measures the number of defect-free products in proportion to all products that were produced at a given time. To calculate it, simply use the formula below:
Example of FTR Final Product Rate’s Calculation
Let’s say that Jim works in a factory owned by Zap Electronics – a fictional electronics manufacturer. Jim’s assembly line operates 7 days a week and produces Zap Swiftbook – a 14-inch laptop.
Last week, Jim’s assembly line produced 7,000 laptops. From this quantity, the quality control officers in Jim’s factory found 40 laptops to be defective. What is the FTR Final Product Rate of Jim’s assembly line?
The quantity of defect-free products: 7,000 – 40 = 6,960
The quantity of all products produced: 7,000
Thus, the FTR Final Product Rate is:
(6,960 / 7,000) x 100% = 99.43%
Jim’s assembly line has an FTR Final Product rate of 99.43%. This means that 99.43% of all laptops produced in Jim’s assembly line last week have successfully passed the quality control process in their first attempt and can be directly sent to distributors. Meanwhile, the rest should be reworked or disposed of.
FTR per Production Phase Rate
Now that we can calculate the defect-free rate of products within a given production time, let’s take one step further. What if we can measure the defect-free rate of an item’s production process?
The FTR per Production Phase Rate is the metric for this matter. It analyzes all phases of an item’s production process and calculates the defect-free rate of each phase. This metric is useful to pinpoint which production phases are the most prone to defects so we can take appropriate measures to minimize defects in these particular production phases.
For manufactured goods, it’s common for an item to be produced in several steps. Even manufacturing the most basic goods still takes several steps to complete.
For instance, making a simple t-shirt involves multiple phases, such as fabric sourcing, dyeing, cutting, sorting, sewing, and label attaching. The FTR per Production Phase Rate seeks to investigate the defect-free rate in each production phase. Here’s the formula:
Example of FTR per Production Phase Rate’s Calculation
For instance, Lucy is the manager of a plant owned by DreamWare Furniture – a fictional furniture manufacturer. Her plant specializes in producing wooden dining tables. Lucy’s plant is operational 7 days a week and produces 350 dining tables/week.
Here are the phases needed to make a fully functional dining table and the number of defects found in each production process last week:
Phase 1: Cutting wood into planks
Number of defective products found: 3
Defect-free products: 347
FTR for phase 1: (347 / 350) x 100% = 99.14%
Phase 2: Carving the wood planks
Number of defective products found: 27
Defect-free products: 323
FTR for phase 2: (323 / 350) x 100% = 92.29%
Phase 3: Painting the carved wood planks
Number of defective products found: 8
Defect-free products: 342
FTR for phase 3: (342 / 350) x 100% = 97.71%
Phase 4: Assembling the processed wood planks into a dining table
Number of defective products found: 15
Defect-free products: 335
FTR for phase 4: (335 / 350) x 100% = 95.71%
Phase 5: Varnishing the dining table
Number of defective products found: 11
Defect-free products: 339
FTR for phase 5: (339 / 350) x 100% = 96.86%
By calculating the FTR per Phase, we can analyze which phases require extra attention due to their relatively higher defect rate than the other phases. In this example, we can see that the second phase (carving the wood planks) has the lowest FTR rate and the highest defect frequency.
Carving wood planks are indeed more prone to defects compared to other phases. This phase is 100% done by human workers and fully relies on the workers’ skills. Meanwhile, machines fully or partially do other phases – which explains their higher FTR rate and lower defect frequency.
As a plant manager, Lucy can put this data to good use. She can lower the defect frequency in the wood plank carving phase through various means. One example is using wood stamping instead of carving to decorate her dining tables. Not only is this method less prone to defects, but it’s also faster and costs less.
First Time Right and Lean Manufacturing
First Time Right is a part of lean manufacturing – a doctrine aimed at optimizing and boosting any manufacturing facility’s production performance. To achieve this purpose, 8 types of waste must be removed, which are:
- Defective Products
- Excessive Processing
- Idle Resources
- Having to Store Items
- Unnecessary Motions
- Underutilized Human Resources
In order to remove these 8 types of waste and become a lean manufacturer, these 5 principles must be implemented in this particular order:
- Identifying What Your Customers Value
- Value Stream Mapping
- Creating a Lean Manufacturing Flow
- Establishing a Pull System
- Kaizen (Continuous Improvement)
Find out more about the 5 lean manufacturing principles.
The modern lean manufacturing doctrine was founded by a Toyota industrial engineer named Taiichi Ōhno. In 1956, he came to the US to visit automobile factories there. During his visit, he learned of the strengths of the American automotive manufacturing system, as well as their weaknesses.
Additionally, he was impressed by the then-new concept of supermarkets. In a supermarket, a customer can “pull” a product from the shelf. Afterward, a store worker will simply refill the depleted shelf, and this process will just repeat itself.
Backed by this experience, he developed the world-famous Toyota Production System and the lean manufacturing doctrine that we know today. The Toyota Production System also has several derivative philosophies, including Kaizen, Jidoka, Heijunka, and the Just-in-Time Production System.
Sometimes, the term “lean manufacturing” is used interchangeably with “agile manufacturing.” Despite their similar names, lean manufacturing and agile manufacturing are separate doctrines. Find out more about agile manufacturing vs lean manufacturing differences.
The Toyota Production System is indeed a powerful doctrine. Deryl Sturdevant, a former President and CEO of Canadian Autoparts Toyota (CAPTIN), wrote an example of its impact in this McKinsey article. According to him, it took 4-5 hours to change a metal die used to make aluminum alloy wheels. With the Toyota Production System implemented, this task can be done in less than an hour.
Thanks to this kind of improvement, Toyota is able to dominate the global auto industry. In 2022, Toyota was crowned the world’s best-settling automotive manufacturer – a title it has held for 3 consecutive years.
The DMAIC Method
Now that you’re able to calculate your plant’s FTR metrics, the next question is: how can you improve your plant’s FTR rate?
Well, there are various methods that industrial engineers worldwide use to increase a plant’s FTR rate. The most well-known one is the DMAIC method.
DMAIC is a popular method used to improve an existing production process. The method’s name is an abbreviation of all of the phases of DMAIC, which are:
In the define phase of DMAIC, a goal is defined. A goal can mean eliminating a problem, such as having less frequent machine breakdowns.
Alternatively, it can also mean improving a certain aspect of production, for example, increasing the number of items produced per minute or cutting the time needed to produce an item.
Regardless of the goal, they must be measurable by a Key Performance Indicator (KPI). It’s also recommended to make a DMAIC roadmap that includes all the planned DMAIC phases and their timeline. This helps you keep track of your DMAIC progress and minimizes delays along the way.
There are various ways of deciding which KPIs to improve. For starters, you can consult your shop floor workers and ask their opinion on what can be improved in the production process.
Alternatively, you can contact your sales or customer relationship department and ask them what the most common customer complaints are. These insights give you a clearer picture of which KPIs to improve.
In DMAIC’s measure phase, you’ll use the KPIs that you’ve gathered in the define phase. Go to the shop floor and measure the existing KPIs of your production process. Afterward, gather this data into a single document – so you can easily access and analyze them later.
In the analysis phase of DMAIC, you’ll use the KPIs that you’ve gathered in the measure phase. If the selected KPIs include fixing a problem, do a root cause analysis to uncover where the issue lies.
If the selected KPIs focus on improving something, you can conduct a Kaizen Blitz with the relevant employees. Afterward, develop a plan to implement the findings of your root cause analysis or Kaizen blitz.
The improvement phase of DMAIC involves executing the results of your root cause analysis or Kaizen blitz. Remove the targeted problems or improve an existing element of a production process.
In DMAIC’s control phase, all improvements that have been formulated and executed in the previous phase are to be documented and standardized. Documenting them means taking notes, images, or videos of what has been done. Gather this documentation in a platform easily accessible by everyone, such as in a corporate Google Drive or Microsoft Sharepoint.
Meanwhile, standardizing them means converting your improvements into a standardized practice that your employees will do every day. The easiest way is by converting your findings into work instructions or a Standard Operating Procedure (SOP). Thus, your improvements will remain permanent, and the previously existing problems will not reappear.
Emma is the manager of a plant owned by Ostrich Tires – a fictional tire manufacturer. Her plant produces 21-inch car tires. She noticed that customers and tire distributors often complain about the frequency of defects in Ostrich Tires’ 21-inch car tires, which negatively affects the customers’ driving safety and experience.
Realizing that changes must be made, Emma underwent the DMAIC method in her plant. Here’s what it looks like, phase by phase:
Define phase: First, Emma must know which KPI she’ll use in her DMAIC process. As the main concern is the high frequency of defective tires, she decided to use the FTR per Production Phase Rate as her KPI.
Measure phase: Afterwards, Emma must measure her plant’s current FTR per Production Phase Rate. To do this, she consulted with her shop floor workers and sought data on defect prevalence in each production phase. Later on, with these data, she calculated the FTR per Production Phase rate for all tires made in her plant.
Analyze phase: In this phase, Emma and her team must analyze the findings from the previous phase. Based on their analysis, she found that most defects occur during the curing phase of the tire production process. To investigate why most defects occur in this phase, she undertook a root cause analysis.
A 21-inch tire needs 16 minutes of curing in a curing machine. While waiting for the curing process to complete, employees often leave the curing station to do other things, such as doing other tasks, getting drinks and snacks at the cafeteria, or simply chatting with their colleagues. As a result, some tires spend too much time curing, leading to defective tires.
Improve phase: Based on her insights in the analysis phase, Emma decided to install an alarm system in the curing station. Thus, an alarm will ring whenever a tire has finished its curing process. Additionally, an alert light will also flash. Consequently, her employees will always be notified by these audiovisual signals when it’s time for a tire to be removed from the curing machine.
Control phase: In addition to the alarm system, Emma also updated her SOP. There, all employees are instructed to remain in the curing station until the tire that they’re working on has finished the curing process. Moreover, she also attached several posters in and around the curing station, instructing workers to remain on the curing station until their work is done.
Not sure whether implementing manufacturing in your plant is worth the cost and effort? Check out our guide to lean manufacturing metrics and ROI measurement.
First Time Right Tools
Conventional industrial tools and methods are insufficient to have a sky-high FTR rate. You’ll need the support of powerful industrial software such as Azumuta. Here’s how our software will help you boost your FTR rate:
Digital Work Instructions
In the final phase of DMAIC, all progress made must be documented and standardized. This includes your work instructions. And there’s no better way of doing so than using our Digital Work Instructions module.
With our platform, you can make easily understood, 100% paperless work instructions in just a matter of minutes – thanks to our drag-and-drop interface. Back your digital work instructions with visual elements such as photos, videos, symbols, and even 3D models.
Use it to standardize your work instructions and share them with your employees’ PC/tablet/smartphone. Thus, the progress that you’ve made in your DMAIC process will remain for good.
Furthermore, our module goes beyond delivering visually intuitive digital work instructions. Our users can communicate with each other and capture real-time images & videos with our module.
With this feature, you can always remain in touch with all of your employees and stay up-to-date with whatever is happening on the shop floor. This module also provides the platform for your shop floor workers to share their concerns and report any issue they see – allowing rapid problem detection & resolution.
Audits & Digital Checklists
When calculating the FTR rate, you’ll need to gather an enormous amount of data, particularly concerning your production and defect rate statistics. That immense flow of information can be overwhelming and will render your employees prone to commit data entry and calculation errors.
Fortunately, you can minimize the possibility of human errors using our Audits & Digital Checklists module. Use our simple yet feature-rich digital checklists to error-proof any data-gathering activity. Thanks to our drag-and-drop interface, you’ll only need to input the necessary data, while our software will do the rest.
With this module, you can experience fully automated Quality Management. Connect your shop floor peripheral devices and let them feed real-time data to your PC, tablet, and smartphone.
Thanks to this feature, you’ll be constantly updated with all the shop floor’s relevant metrics. Then, visualize this data with our data visualization dashboard. This feature will be especially useful in the measure and analyze phases of DMAIC, as all necessary data are accessible within just a few clicks.
Should an issue have been detected in your DMAIC process, you can easily undergo root cause analysis with our Quality Management module. Use our ticketing & product orders systems to pinpoint the root of the issue, allowing you to resolve it swiftly.
Skill Matrix & Training
To consistently have a satisfactory FTR rate, your employees must always be regularly trained and have sufficient skills. After all, they’re the ones who run your plant’s day-to-day operations.
Using our Skill Matrix & Training module, you can plan your employees’ short and long-term training programs in an instant. With this module, you can set your employees’ training schedule, select the participating employees, share the training materials, and send automated notifications to their devices when training is due – all under one module.
Besides training them, it’s also necessary to check their skill levels occasionally. That way, you’ll immediately know if there’s a skills gap in your organization. Our skill matrix will immediately inform you in which employees and in which skill field this skills gap lies.
With our skill matrix module, you don’t have to draft the matrix from scratch. Simply input your data into our pre-made template, and our software will do the rest. Our skill matrix will automatically calculate the average skill level of each employee and color-code them for extra visual intuitiveness.
To boot, our Skill Matrix & Training module can also generate individual employee reports – complete with their personal data, skill levels, and training history. Thus, you don’t have to manually create one yourself, saving your precious time for other, more important tasks.
Free Lean Manufacturing and Quality Management System E-Book
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See how Azumuta’s powerful modules have helped a client to have a 100% paperless shop floor, 100%, 60% reduction in data entry time, 35% reduction in documentation time, and achieved 0% operator idle time.