Methods that are used in today’s industry

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Theoretical Principles

In this chapter, we have collected some widely used and well-known theoretical methods that are used for product development. We have portrayed the methods of Value Analysis, Quality Function Deployment, Failure Mode and Effects Analysis, Design for Assembly and Modular Function Deployment in a descriptive manner in the following passages.

Value Analysis (VA)

After the World War II, intensive developments of new technologies were required. Even questions about new quality assurance and assertion started to arise, gaining a new interpretation, as well as attaining more attention around the world. In the 1950s people began to study and see that both the quality and cost efficiency could already be influenced during the construction phase of a product. The value of a product became defined as the relation between performance and cost. These ideas were elaborated by Lawerence D.Miles and he created the method called Value Analysis (Johannesson et al. 2004).
The purpose of this method is to discover the cheapest manufacturing method for a product and at the same time trying to find the best alternative which can keep the same functionalities for the lowest price. During this analysis similar question as the following are asked:
• What is the main function of the product?
• How much does it cost?
• Which alternative solutions exist?
• How much will the cost be for the alternative solution?
When those questions are answered comes the time to choose the alternative with the lowest cost that simultaneously keeps the same functions of the product. Another important advantage with the VA method is that it enables traceability that didn’t exist before, in other words everything that is done gets documented and becomes easy to retrace (Johannesson et al. 2004).

Quality Function Deployment (QFD)

Manufactured products primary has the purpose to please and satisfy the customer and market. Therefore everything that is produced should be adapted after the customer and market needs. Thus, it is essential for the manufacturing to be able to translate from customer needs to a more measureable and technical parameters. (Asif, 2012)
QFD is an instrument that does this translation. QFD was introduced in Japan by Dr. Yoji Akao (1966). He stated that QFD is “a method to transform user demands into design quality, to deploy the functions forming quality, and to deploy methods for achieving the design quality into subsystems and component parts, and ultimately to specific elements of the manufacturing process.”
The car industry is an example of where the method is put into good use. With the help of QFD they could find the best components of a car to modify, such as the car doors, wind shield or rear-view mirror, after the needs of their client. This method is more beneficial for products that need further development and less suitable for completely new products.
The House of Quality for Enterprise Product Development Processes is a technique and tool based on QFD. It is a matrix that apart from showing the customer requirements and quantified construction specifications also includes a competitor analysis (benchmarking) where the company can see its strengths and weaknesses compared to its rivals (Johannesson et al. 2004). The matrix comprise of four points of interest:
• Market survey – to find the customers’ need, demand and expectation
• Benchmarking – to find the strengths and weaknesses compared to the competitors
• Identify its own priorities for development
• Translate the customer demands to quantitative specifications for construction and manufacturing
Figure 1 is an example of how a House of Quality matrix can look like. Note that the four points of interest previously mentioned is distributed into nine different sections of the matrix below.
However, there are several difficulties in the application of some parameters. Among them includes interpreting the customer voice, defining correlations between the quality demanded and quality characteristics (Carnnevalli et al. 2008). This method is therefore more of a foundation and support for discussion and documentation within product development than a stone set rule to follow (Johannesson et al. 2004).
Figure 2 is an example of the house of quality matrix for car doors that was mentioned in an earlier paragraph of this chapter.
Figure 2: House of Quality Matrix for Doors (Biren Prasad, 1998)
It can be concluded that with the support of the QFD method we can find out the customer demands and wishes, and translate this to a more technical and measurable parameter. From the parameters it is possible to find the requirements to meet the customer needs. Another advantage of QFD is enabling traceability for the solution of product development due to the fact that everything is neatly documented.


Benchmarking is the process of comparing one’s business processes to best practices from other organizations and companies. This can be within the same industry but also with other businesses in order to continuously make improvements from what has previously been accomplished (Ax et al. 2010). Benchmarking can be done on basically any area, from the functionality of the products to logistics within transportation. The direction and focus of benchmarking can also vary depending on which results are desired.
There are three benchmarking methods that will be mentioned. The first one can be categorized as “internal benchmarking” where you benchmark internally within the same company or underlying companies, and can be done between the departments as well. The second one, ”competition oriented benchmarking” is where you compare your own company to other companies that are within the same market or has their attention directed towards the same customer groups. This method is seen to be more effective than the internal method. The third version of benchmarking is called “function targeted benchmarking” or just “general benchmarking.” This method is externally radiated, similar to the “competition oriented benchmarking”. The difference is that you don’t necessary study the companies within the same business or industry but instead companies that have exceeded in performance within any known areas. The focus is put on functioning, manufacturing, administration and marketing. This is because it doesn’t matter which business these areas are belonged to since they are rather general and possible to apply for most business niches (Ax et al. 2010).

Failure Mode and Effects Analysis (FMEA)

The FMEA method is based on subjective and relative evaluations of imperfections and errors that can appear on a product and the consequences that can arise from it. This method is centered on errors that have a chance to appear on the component level and how it eventually can affect the whole system. The FMEA identifies all the possible errors that can occur. The three factors that this method brings forward are the probability of error, degree of severity, and probability to discover or not discover the error. By working with subjectively rough estimates, this method can already be used on early stages of the development of the product. An important part of this analysis is to prioritize the biggest errors and problems which can arise, and then later in turn amend the problem. The FMEA is used within two areas. The first one and also the more common one is called design-FMEA. It means to run an analysis during the construction works. The second one called process-FMEA is used during the processing of a product.
The three factors that were previously mentioned are extracted with relative scales and can look similar as below:
• Probability of error
1 = Very small probability that the error occurs
4 = There is a certain probability that the error occurs 10 = High probability that the error occurs
• Degree of severity
1 = negligible influence on the product and the user won’t notice
4-6 = quite serious influence and the user will notice the error 10 = Very serious consequences and dangerous for the user
• Probability to not discover the error
1 = the error will quite easily be discovered
4-6 = the error might be discovered
10 = there is a high chance for the error to not be discovered at all
After all these factors are accounted for, the Risk Priority Number (RPN) is calculated. The RPN is calculated through multiplication of the three factors, and will become a number between 1 and 1000. The FMEA method brings forward the basic data for prioritizing the errors that needs to be addressed. After the RPNs are established for the different types of errors, suggestions of how to remedy the errors with the highest RPN are then made, and new RPNs are again extracted from that (Johannesson et al. 2004). All this information is documented in the FMEA table. An example of how a FMEA table can look like can be seen in figure 3 below:
Figure 3: FMEA Template (Velaction Continuous Improvement, 2009)
As for all other methods, FMEA has both advantages and disadvantages. The method enables the user to prioritize the errors which need to be addressed and early corrections can prevent more serious future errors. The FMEA strengthens the cross-functional collaboration within product development. But there are disadvantages with the method since it bases on relative and subjective evaluations of the consequences and risks. Moreover, the method doesn’t consider the connection between the different errors and sees them as unrelated to each other (Johannesson et al. 2004).

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Design for Assembly (DFA)

Design for Assembly is often used to obtain a higher degree of product adaptation. As the name of the method states, the components are designed in such a way which makes assembling as easy as possible. This is usually done during the manufacturing and development of a product.
The way of DFA was very much accentuated and developed during the end of the 1980s in USA. Many variants of this method have been branched from the original. Some examples of it are: Design for Manufacturing, Design for Injection Molding, Design for Quality, Design for Service, Design for Environment and so on. New methods based on DFA have also been developed by companies that want to adapt to their own assembly procedures. For instance Hitachi has established a new system called Producibility Evaluation Method (PEM), as well as Sony and Sharp have been developing their own assembly adaptation methods (Johannesson et al. 2004).
The first thing that is done during DFA is to evaluate the most profitable assembly method from a cost perspective and at the same time take the production volume, flexibility and the time between readjustments into consideration. There are three major assembly methods that exist. The “automatic assembly” is used during large volume production (million products/year). “Robot assembly” is used when a higher requirement of flexibility on a product is needed. The final one “manual assembly” is most suited for when the volume quantity is small enough or when the assembling is too advanced for robots (Johannesson et al. 2004).

Design for Automatic Assembly (DFA2)

Design for Automatic Assembly is commonly categorized as an under category of DFA. DFA2 is DFA but directed towards automatic assembly. The equipment for manual and automatic assembly does vary a lot. Manual assembly is the use of human capabilities with or without the aid of the sophisticated jigs, fixtures and power tools to perform the assembly task (Redford 1983). A human has capacity and traits in flexibility of movements, power, speed, and has good sense of touch and sight which makes certain operations only possible or more suitable for the human being compared to robots (this fact is reserved for change in the future). The machines on the other hand exceed humans in terms of steadier quality because of its repeatability, and it can work without the need for breaks (Eskilander, 2001).
Maffei (2012) states that “DFA2 should be put into use early for product development, preferably already during the design phase until the finished product in order to minimize and eliminate future changes.” Notably products which are suited for automatic assembly can also be assembled manually (Eskilander, 2001). Apart from finding the best method, issues concerning the environment should also be considered during this process. Before actually introducing the final solution, it also has to be economically viable (Maffei, 2012).

Modular Function Deployment (MFD)

As competition from every corner holds a tighter grip on companies and harder requirements are put on the prices and quality, it has become imperative to take as much advantage as possible on the resources that exist. In order to combat this, the companies try to expand their market share through extending their offers and supplies with the help of presenting a larger variation and higher quality of their existing product range and at the same time trying to decrease the manufacturing cost per unit (Johannesson et al. 2004).
A good solution to this is to design the products in such a way that the components for the main product can be included in various combinations. Also that the components can be mixed and matched in a variety of configurations depending on what functions the product want to have. This means that with a limited number of components a company can achieve great variation in the production for different products of the similar series. In other words, by picking and choosing among an array of compatible components, the consumer can move freely around a large area of the product space (Langlois et al. 1991). This is the strategy of modular function deployment, in addition, it grants economic benefits in the development, production and service. The positive advantage and effect with the interchangeable “modules” are (Johannesson et al. 2004):
• The time for development decreases
• Less risk, especially when you want to develop a product with new functions
• Less lead time during the manufacturing process
• Higher quality
• Less article number to administer
A systematic method that has been developed for the MFD consists of five parts. The method largely based on the forth mentioned QFD and DFA. The five parts are the following (Johannesson et al. 2004):
1. QFD for the control of customers’ need and benchmarking to know the competitive situation
2. Part function based generation of technical part solutions
3. Identification of possible modules with the Module Indication Matrix (MIM)
4. Examination and evaluation of the suggested modular division/classification
5. Component construction of muddles with DFM and DFA methods
Along with the advancement of technology come parts and components that need to be replaced and reconstructed. The MFD makes the whole process easier due to the interchangeable modules. Less effort is needed on meeting the customer requirements because it will be easier to combine and produce what the customer wants with MFD.

Table of contents :

1. Introduction
1.1 Overview and History
1.2 Purpose
1.3 Research Questions
1.4 Delimitations
1.5 Method
1.5.1 Literature studies
1.5.2 Interviews
2. Theoretical Principles
2.1 Value Analysis (VA)
2.2 Quality Function Deployment (QFD)
2.2.1 Benchmarking
2.3 Failure Mode and Effects Analysis (FMEA)
2.4 Design for Assembly (DFA)
2.4.1 Design for Automatic Assembly (DFA2)
2.5 Modular Function Deployment (MFD)
2.6 Earlier Studies
3. Methods that are used in today’s industry
3.1 Atlas Copco Tools
3.1.1 Profitability calculations and the view of Value Analysis
3.1.2 Development with customer as focus
3.1.3 Error Analysis – Risk analysis a more appropriate method than FMEA
3.1.4 Assembly
3.1.5 Modular System – Future method of product development
3.1.6 Environment
3.2 Scania
3.2.1 Value Analysis – A question of fashion
3.2.2 Quality and Customer – Scania and Rivals
3.2.3 Error Analysis – Focus on FMEA
3.2.4 Assembly
3.2.5 Modular System – Veteran Scania
3.2.6 Environment
3.3 ABB – Force Measurement Department
3.3.1 Value Analysis – Cost vs. Performance
3.3.2 Customer and Quality – Basic functions and unique measurement principles
3.3.3 Error Analysis – Trial by customers
3.3.4 Assembly
3.3.5 Modular System – Software Modularization
3.3.6 Environment
4. Similarities and Differences between Practice and Theory
4.1 In Context of Value Analysis (VA)
4.2 In Context of Quality Function Deployment (QFD)
4.3 In Context of Failure Mode and Effects Analysis (FMEA)
4.4 In Context of Design for Assembly (DFA)
4.5 In Context of Modular Function Deployment (MFD)
5. Conclusion – How applicable are the theoretical methods in practice?
6. Discussion
6.1 How to improve the product development
6.2 What will the future look like?
7. Critical Assessment
8. References
8.1 Books
8.2 Articles
8.3 Reports
8.4 Persons
8.5 Websites


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