Q 579.  Robust Design - What is a Robust Design? What tools does it use to improve the reliability and performance of the product/process? Provide some examples of products developed using this technique.

 

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Robust Design is an engineering concept. It is used to develop reliable products or processes that are closest to the customer specifications and needs. This concept looks at reducing variation to the maximum. It also looks at covering changes in any aspect of the product or process like sudden change of dimensions or requirements by the customer or other environmental factors.

 

List of some of the tools used under this concept:

Design of Experiments (DOE): DOE is a statistical tool that studies the relationship between input and output variables. This ensures that minimum run of experiments are done to achieve the output that matches the customers specifications.

 

Quality Function Deployment (QFD): QFD is a method that helps translate customer requirements into specific product or process characteristics. It ensures that the design reflects customer needs and preferences, thereby enhancing customer satisfaction. House of quality is the basic design tool of QFD.

 

Failure Mode and Effects Analysis (FMEA): FMEA is a structured approach to identify and address potential failures in a process or product. This single point of failure analysis tool helps to assess the severity, occurrence and detection of failure modes and rank them to apply countermeasures on priority.

 

Robust design principles can be applied to various industries to improve the reliability and performance of products and processes. Some examples of products developed using these principles are indicated below:

 

High End Cars: Motor car manufacturers develop cars that are reliable and perform consistently under different road and weather conditions. While designing these cars a lot of customer requirements (implied or not implied) are tested against these principles/tools. It ensures customers comfort and safety along with other features.

 

Smartphones: Customer dynamics are changing everyday when it comes to smartphones. Manufacturers thrive on the same and ensure that the principles of robust design are adopted to create the best in class phones with a lot of features.

 

Robotics in hospitals: Robots performing surgery is a complex and dangerous proposition giving that a life is in hands of a machine. However the deployment of such robots go through an extensive experimental methodology before being delivered.

 

Pharma Industry: Medicines manufactured in the pharmaceutical companies go through a lot of experimentation and research before being sent to the final consumers.

 

Introduction to Robust Design – Robust design is an experimental design run to study the interaction between control and uncontrollable noise factors and alert the control factors to minimize response variation from uncontrollable factors to develop high quality product/process with minimal cost. Basically, a design that has minimum sensitivity to variations in uncontrollable factors (noise factors). Robust design also known as Taguchi method as the design is pioneered by Dr. Genichi Taguchi. Considering the noise factors and the cost of failure in this method helps to enhance customer satisfaction at low cost. Robust design focuses on improving the fundamental function of the product or process, it is the most powerful method available to reduce product cost, improve quality and simultaneously reduce development interval. A robust design aids in variation reduction that leads to productivity improvement and ensures reliability. Robust design thinking is to develop high quality products and process at low cost with increase in customer satisfaction.

 

Tools used for Robustness Strategy -

1.      P-Diagram

2.      Ideal Function

3.      Quality Loss Function

4.      Signal to Noise Ratio

5.      Orthogonal Arrays

 

1.      P-Diagram – This diagram provides the classification of the variables associated with the product which has inputs like noise, control, signal and output as response factor. P-diagram is used in every project/product development lifecycle. List out all the input and output factors and then consider the factors that are beyond the control of the design which are noise factors and the parameters that are specified by the designer are control factors.

2.      Ideal Function – This function is used mathematically or statistically to identify the ideal form of the signal response relationship associated by the design concept for making the higher level system work perfectly.

3.      Quality Loss Function – Known as Quadratic loss function which is used to measure the loss incurred by the user/consumer due to deviation from target performance.

4.      Signal to Noise Ratio – This is used to predict the quality of field by going through systematic lab experiments.

5.      Orthogonal Arrays – This is used for gathering dependable information about control factors (design parameters) with a minimal number of experiments.

 

Following are the main steps for Robust Method –

 

1.      Problem Formulation – In this stage, we identify the main function, develop the p-diagram, select the ideal function and signal to noise ratio and finally plan the experiments to run. We run minimal experiments to alert the noise, control and signal factors for ideal design.

2.      Data Gathering –  In this stage, the factors data is gathered after alteration which helps to run the experiments that are required for the ideal design implementation. Basically, to run the test experiments at low cost.

3.      Factor Effect Analysis –  In this stage, we read the outcome of the control factors to identify the most favorable arrangement of the control variables/factors.

4.      Prediction/Confirmation – In this stage, the performance of the design is predicted under the most favorable arrangement of the control variables/factors to confirm the best conditions are met. The real time experiments are run to confirm there is no variation in the results for the implemented design. If the results do not match, the process needs to be repeated.

Robust means something is sturdy or able to hold up which is an important quality to have in a product because the customers want a product, they can trust and depend on.

Robust design is a quality engineering approach that companies use to specifically focus on eliminating or reducing variations in products or a process. it uses statistical methods and experiments which may not eliminate the causes of variation but reduces their effects. it also involves continuous customer focus and design optimization. It can help to create low-cost, high-quality products and processes, and to gain a competitive advantage and a reliable brand image.

 

In simple words, the overall objective of a Robust Design is to make a sound and successful design which is acceptable to the customer and the market.

 

Tools:

1.) FAST Diagram approach: Function Analysis Systems diagram explains a logical relationship between how functions are linked together to deliver required service to produce a product. It answers the questions Why to perform this function, how to perform it and when is it to be performed. It helps analyzing complex systems, and narrowing down the conclusions of the functions performed into the essence of the tasks that must be delivered. It is a creative thought process which enhances communication among team members.

 

2.) CAD: Computer Aided Designing is used to create highly accurate 2D and 3D models which included all steps in the design process beginning from creation and modification to analysis and design. It is very useful in delivering precise, high-quality visualizations and is easy to understand. Every step of the design process is documented, including measurements, angles, and dimensions which can also be referred to in the future.

 

3.) QFD: Quality function deployment is a method used to translate voice of the customer into product translated to engineering characteristics of the product and service and after that plans to produce the products that fulfil customer requirements. Design engineers often begin with a gradual drill-down method with planning the development and go through four phases to gain a deeper grasp of the necessary process control and quality.

 

4.) DFMEA: Design Failure Mode and Effects Analysis identifies the design functions, Failure modes and their impacts on the customer with associated severity ratings and danger of the impact. The detection grade emphasizes how effectively particular tests can verify that the failure mode and its causes have been removed. The DFMEA keeps track of improvements through reduction in the Risk Priority Number (RPN). An improvement and risk mitigation history can be recorded by comparing the before and after RPN.

 

5.) Response Surface Methodology (RSM): it is a statistical technique that examines the relationship between a number of explanatory factors and one or more response factors. RSM's is a The technique that utilizes a series of planned tests to find the best response. It can be used to improve the design of a product or process by determining the crucial elements that have the greatest impact on performance and then optimizing these elements.

 

Examples for Robust design

1.) Developing separate fuel pump nozzle for diesel and gasoline so that people do not mistakenly fill up gasoline powered vehicles with diesel fuel, increasing the risk of accidents.

1.) an umbrella fabric that remains intact when exposed to changing environments (external variation)

Robust design is a methodology that is used to develop products or processes that are highly reliable and is resistant to variations in the operating conditions. This methodology involves designing and optimizing a system to minimize the impact of variability and uncertainties, such as manufacturing variations, environmental conditions, and usage conditions. By reducing sensitivity to these factors, robust design ensures that the product or process remains functional and meets its performance requirements.

 

Robust design uses several tools and techniques

Design of Experiments (DOE): DOE is a statistical method to systematically vary input variables and analyze their effects on the output performance of a system. By identifying the critical factors and their optimal settings, robust design ensures that the product or process remains robust despite variations.

Taguchi Methods: This approach focuses on minimizing the effects of noise/variations on system performance. This method involves the use of orthogonal arrays and signal-to-noise ratios to optimize the design parameters and improve robustness.

Quality Function Deployment (QFD): QFD is a systematic approach that translates customer requirements into specific engineering characteristics. By prioritizing customer needs and aligning them with design features, QFD helps in developing robust designs that caters to customer expectations.

Failure Mode and Effects Analysis (FMEA): FMEA is a risk assessment tool used to identify potential failure modes, their causes, and the effects on system performance. Addressing these failure modes during the design stage, the robust design minimizes likelihood of failures and their impact.

Examples of products developed using robust design techniques:

Automobiles: Automotive manufacturers use robust design to develop vehicles that perform reliably under various driving conditions, such as extreme temperatures, road conditions, and user behaviors. Robust design techniques help optimize engine performance, fuel efficiency, suspension systems, and overall vehicle reliability.

Aerospace Systems: In the aerospace industry, robust design is crucial for aircraft, spacecraft, and related systems. By considering factors like aerodynamics, structural integrity, and varying operating conditions, robust design techniques are used to develop reliable and safe aerospace products.

Robust Design is an engineering approach aimed at creating products or processes that are less sensitive to variations and uncertainties in manufacturing, usage, or environmental conditions. The primary goal of Robust Design is to improve the reliability and performance of a product or process while minimizing the effects of unavoidable variability. This is achieved by designing products that consistently meet performance requirements under a wide range of operating conditions.

 

Meeting customer expectation also under non-ideal conditions. This is particularly important because real-world conditions are rarely constant or predictable and variations can occur due to factors such as manufacturing tolerances environmental changes or user behavior.

 

By adopting this approach, companies can reduce the risk of product failures, warranty claims, and customer complaints, leading to improved customer loyalty and overall business success. Robust Design is particularly valuable in industries where consistency, reliability, and customer satisfaction are paramount.

 

Common examples of robust design include –

• Replacement parts that will fit properly (unit-to-unit variation)
• Umbrella fabric that will not deteriorate when exposed to varying environment (external variation)
• Food product that will have long shelf lives (internal variation)

 

Below are some tools commonly used in Robust Design:

 

1.  Design of Experiments (DOE): DOE allows engineers to systematically vary input factors and measure the corresponding output responses. It helps identify the optimal combination of factors that result in the desired performance and robustness. Henkel Corporation, makers of adhesive, sealant, surface treatment technologies, several years ago switched to the design of experiments (DOE) method. By varying the values of all factors in parallel, DOE drastically reduces the number of runs required to determine the optimal value of each factor. This approach determines not just the main effects of each factor but also the interactions between the factors.

 

2.  Taguchi Methods: Developed by Genichi Taguchi, these methods emphasize the reduction of variability and improving quality during the design phase. These method focus on concept of signal-to-noise ratio (SNR) which quantities relative contribution to variation to overall performance . It is a structured approach to determine the best combination of inputs to produce a product or service based on DoE methodology for determining parameter level. Example – use it to identify factors that affect fuel efficiency and determine optimal setting, the factors being engine turning parameters like tire pressure, vehicle weight and aerodynamic design. Using Taguchi method, the DOE is designed to explore the effect on control factors on engine performance while minimizing the impact of noise factors. 

Instead of having to test all possible combinations like the factorial design, the Taguchi method tests pairs of combinations. Only the main effects and two way interactions are considered in the Taguchi method. The Taguchi orthogonal arrays are based on judgment sampling (using one’s best judgement) and are not randomly generated as with runs for a traditional DOE. With a traditional DOE, noise is treated as a nuisance variable and should be blocked out. Taguchi treats noise as a major focus of analysis.

 

3.  Tolerance Design: Tolerance Design involves determining the allowable variations or tolerances in various components or processes to ensure robustness. Statistical techniques, such as Six Sigma, are often employed to set appropriate tolerances. Example, designing and manufacturing engines, where the goal is to create robust piston design that can accommodate manufacturing variation, thermal expansion and wear while still maintaining optimal performance. It involves analyzing the dimensional and geometric tolerances of various piston parameters such as diameter, height, skirt shape. Tolerance method combined with Six Sigma principles is a powerful approach to achieve robust design.

 

4.  Quality Function Deployment (QFD): QFD is a structured approach that helps translate customer requirements into specific engineering characteristics. It ensures that the design meets customer expectations and provides a framework for robustness considerations. A car manufacturer may identify customer needs such as fuel efficiency, safety and comfort. These needs are translated into specific engineering characteristics such as aerodynamic design, advanced braking system, ergonomic interior. Through QFD, potential sources of variability and uncertainty are identified and addressed resulting in amore robust and reliable vehicle design.  

 

5.  Failure Mode and Effects Analysis (FMEA): FMEA is a systematic approach to identify potential failure modes, assess their severity, detectability, and occurrence, and prioritize actions to mitigate or eliminate them. It helps design robustness by proactively addressing failure risks. There are 2 broad categories of FMEA – 1) Design FMEA – explores possibility of product malfunctions, reduced product life, safety and regulatory concerns derived material properties, tolerances, interfaces with other systems 2) Process FMEA – discover failure that impacts product quality, reduced reliability of the process, customer dissatisfaction, safety and environmental hazards derived from human factors, material used, machine used. In pharmaceutical industry, FMEA can be used to identify failure modes and their effect on the production process such as contamination or incorrect dosing. Manufacturers can use robust design principles such as automated quality control systems or process optimization technique to reduce the likelihood of failures and improve the consistency of pharmaceutical products.  

 

Examples of products developed using Robust Design techniques include:

1.  Automobiles: Automotive manufacturers use Robust Design to create vehicles that can perform consistently across different driving conditions, climates, and manufacturing variations. Car manufacturers use Robust Design to develop engines that deliver consistent performance across different operating conditions, such as temperature, altitude, and fuel quality. Toyota's Prius hybrid car, which was designed to be more reliable and fuel-efficient by reducing the impact of variations in driving conditions. The Toyota Prius, which was designed using Taguchi Methods to optimize fuel efficiency and reduce emissions

 

2.  Consumer Electronics: Companies designing smartphones, laptops, or televisions employ Robust Design to ensure the devices function reliably and consistently under various usage scenarios and environmental conditions. Mobile phone manufacturers implement Robust Design to create devices that maintain reliable performance regardless of user habits, network conditions, or variations in component manufacturing. Apple's iPhone, which was designed to be more durable and less prone to failure by using high-quality materials and designing components that are less sensitive to variations in manufacturing. Whirlpool's washing machines, which were designed to be more reliable and efficient by using advanced control systems that adjust the washing cycle based on the load size and type of fabric.

 

3.  Aerospace Systems: In aerospace engineering, Robust Design techniques are utilized to create aircraft and spacecraft systems that can withstand extreme conditions, variations in fuel quality, and operational uncertainties. Boeing 777: The aircraft was designed using Robust Design techniques, which helped to improve its safety and reliability. The Boeing 787 Dreamliner, which used FMEA to identify potential failure modes and ensure reliability and safety.

 

4.  Medical Devices: Robust Design is crucial in the development of medical devices to ensure their effectiveness, safety, and longevity under different patient conditions and usage scenarios. Medical device manufacturers apply Robust Design principles to develop devices with consistent performance, even when used by different healthcare professionals or in diverse patient populations. A robust cleaning method (either manual or mechanical) use a worst-case approach for the numerous study variables.

 

5.  Industrial Equipment: Equipment used in factories or industrial processes often undergoes Robust Design to handle variations in input parameters, such as temperature, pressure, or load, and deliver reliable performance. Manufacturers of complex industrial machinery use Robust Design to design equipment that maintains precision and efficiency despite variations in input materials and operating conditions.

Robust Design means a product design made  to with stand any future variations in usage environment.

Robust Design can be categorized as concept design ,parameter design and tolerance design.

Taguchi’s Robust design defines a parameter in a band that “noise “ does not cause failure  .

Example of Robust design are the products not having impact due to variation caused by production environment.

 

”Green Design” that takes into consideration sustainability of resources for future generations is an excellent example.

Sustainable design that used sustainable resources socially, economically & environmentally.

 

Robust Design improves fundamental function offering flexibility in engineering by considering noise factors such as environmental variation due to product’s usage, manufacturing variation and component deterioration.

A survey conducted by ITT industries indicates that design influences around 70% of the product’s life cycle cost.

The product development effectiveness can be increased by Robust design using value engineering.

 

By addressing variation reduction in a specific stage of a product/process design , one can prevent the downstream failures.

4 steps followed in Robust parameter design are

1>Problem Formulation,2>Data collection , simulation 3>Factor Effects Analysis, 4> prediction confirmation.

 

 

Below is example of a Robust design strategy during a product manufacturing.

Differential amplifier used in coin telephones has the problem of excessive offset voltage due to manufacturing variability.

High offset voltage causes poor voice quality , To minimize the field problems Robustness was adopted during mfg.,

The nominal values of the critical parameters was set such that circuit’s function becomes insensitive to manufacturing variation.

Robustness strategy uses following tools – P Diagram, Ideal Function , Quadratic Loss Function , Signal to Noise ration and orthogonal arrays.

An Image of the Green Design which utilizes sustainable resources and inputs to give a sustainable output of the product design is nothing but facial creams made of natural and ayurvedic herbs grown in farms. Here instead of using chemicals , By using a farm grown input and natural resources , we are doing a sustainable business without harming environment.

While all the responses are commendable, Ankur Sarkar has emerged as the winner primarily because of his specific and relevant examples.