MN5620 | Research Methods for Engineering Projects

Introduction

In the context of the assignment, there are three different parts on which the research is to be done. In the first context, the consumer needs and concerns are to be assessed with the help of the data provided. The unique selling point is to be assessed. The assignment is on the sales of a motor vehicle company. In the second part of the assignment, the research of the consumers’ spent time on the internet.

Part 1: Understanding Customers

a. (i) Interest in Electric motorcycles for three groups

Electric motorcycles are used for help in the transport system which is decarbonizes. It is used for accessing the potential. It is fully accessed from the potential of the motorcycle. It needs further research which is based on the preferences of users and it fit on the factor range which can be contributed to the people and make the use of low carbon vehicles (Krishen et al. 2017, p. 20).

For 5 to 8 years (Segment A), the medium mileage is required to be 10000 to 20000/per year. Every year, the number of cars on the road is increasing exponentially. Americans drive more and more miles (Niu and Wang, 2016, p. 874). The average miles driven per year by motorists in the United States are at an all-time high. For those benefits people are preferred to select the medium mileage of electric motorcycles.

For till the end (Segment B), this is referred to the highest mileage which generally based on the production purpose. The production is based on the depreciation which is solely the result. The passage of time plays has no role in the entire process. An estimate useful life is 90,000 miles. So the cost is

Description Expense = Cost – Residual value / Estimated Units of Useful life

                               = $20000 - $ 2000/90000 = $ 0.20/ mile

For less than 3 years (Segment C), the deprecation amount is increasing annually and each year it is related to the unit.

There are some people who like to have the latest safety and technological innovations in the cars they drive. Getting a new car every 3 or 4 years guarantees user enjoys the latest bells and whistles cars have to offer.

There are certain reasons for getting a new car in 3 or 4 years, and then leasing can be a great choice for the user. If one is like to finance a car with a typical 60-month loan, and decided which is wanted to trade it in for a new one after 3 years.

(ii) Customer Perspective and Identifies the Needs

Current sales are based on similar types of vehicles which are mainly used for the battery packs. Here, it is divided into three parts based on mileage such as low mileage, medium, high mileage (Sebald and Jacob, 2018, p. 40). The production cost is based on various scales of economics and has electric packages with an internal combustion engine.

 

Segment Data

Annual Description Rate

Low Mileage

0.845

Medium Mileage

0.834

High Mileage

0.720

 

Table 1: Segment Data and Annual Rate

(Source: Erevelles et al. 2016, p. 897)

 

b. Field Research consumer reaction in USP

 

The field research takes place in a practical environment that has the participants such as a store, work, bank and many more (Yurova et al. 2017, p. 271). The researcher can gain a lot of insight models and hoe it plays a role in an individual’s life. Observation of participants, data collection from video and interviews are used in the field research.

Part 2: Quantitative Data Analysis

a. (i) Use Standard Deviation for examining the other usage

The user has to do the sum of the deviance (sd^2*n) of each of the groups then also required to make the calculation of deviance of three groups (Zhang et al. 2017, p. 21). It means the user needs to calculate the mean of means and the deviance of the weighted means. Therefore,

Total Variance = Total Deviance of whole group/ (n1+n2+n3)

Then, use the square root and the actual formula will be

Consider the set for Segment A = {6.75, 7.46, 5.32, 7.85, 6.36}

Mean = Sum of X values/N(Number of Values)

          = (6.75+7.46+5.32+7.85+6.36)/5

         =   33.74/5

         = 6.748

Hence, the mean = 6.748

For finding the variance, subtract the mean value from each value.

6.75- 6.748= 0.002

7.46- 6.748= 0.712

5.32- 6.748= -1.428

7.85- 6.748= 1.102

6.36- 6.748= -0.388

Now square the answers for getting the subtraction.

(0.002)2 = 0.000002

(0.712)2 = 0.506944

(-1.428)2 = 2.039184

(1.102)2 = 1.214404

(-0.388)2 = 0.150544

Add all the square numbers

0.000002+0.506944+ 2.039184+ 1.214404+ 0.150544

= 3.911078

Divide the sum of squares by (n-1)

3.911078/ (5-1) = 3.911078/4 = 0.9777695

The variance is 0.9777695

Now, the square root of the variance is

?0.9777695= 0.98882

Hence the standard deviation of Segment A is 0.98882

 

Consider the set for segment B = {6.86, 8.48, 7.42, 8.12, 6.54}

Mean = Sum of X values/ N (Number of Values)

          = (6.86+8.48+7.42+8.12+6.54)/5

          = 37.42 / 5

          = 7.484

Hence, the mean = 7.484

For finding the variance, subtract the mean value from each value.

6.86- 7.484= -0.624

8.48- 7.484= 0.996

7.42 - 7.484= -0.064

8.12 - 7.484= 0.636

6.54 - 7.484= -0.944

Now square the answers for getting the subtraction.

(-0.624)2 = 0.389376

(0.996)2 = 0.992016

(-0.064)2 = 0.004096

(0.636)2 = 0.404496

(-0.944)2 = 0.891136

Add all the square numbers

0.389376+0.992016+ 0.004096+ 0.404496+ 0.891136

= 2.68112

Divide the sum of squares by (n-1)

2.68112/ (5-1) = 2.68112/4 = 0.67028

The variance is 0.67028

Now, square root of variance is

?0.67028= 0.81871

Hence the standard deviation of Segment B is 0.81871

 

 

Consider the set for Segment C = {4.23, 3.75, 4.02, 3.25, 6.31}

Mean = Sum of X values/N (Number of Values)

           = (4.23+3.75+4.02+3.25+6.31)/5

           = 21.56/5

           = 4.312

Hence, the mean = 4.312

For finding the variance, subtract the mean value from each value.

4.23 - 4.312 = -0.082

3.75 - 4.312 = -0.562

4.02 - 4.312 = -0.292

3.25 - 4.312 = -1.062

6.31 - 4.312 = 1.998

Now square the answers for getting the subtraction.

(-0.082)2 = 0.006724

(-0.562)2 = 0.315844

(-0.292)2 = 0.085264

(-1.062)2 = 1.127844

(-1.998)2 = 3.992004

Add all the square numbers

0.006724+ 0.315844 + 0.085264 + 1.127844 + 3.992004

= 5.52768

Divide the sum of squares by (n-1)

5.52768/ (5-1) = 5.52768/4 = 1.38192

The variance is 1.38192

Now, square root of variance is

?1.38192 = 1.175

Hence the standard deviation of Segment C is 1.175

 

Standard deviation is the calculation for measuring a dataset that is relative to the mean value. It is required to calculate the square root of the variance (López et al. 2018, p. 180). The standard deviance is mainly used for the measurement of any statistical problem. Here we get the solution of SD of segments A, B, and C which are referred to the Segment 5, 9 and 1. The results are based on the time spent which is average for different households.

(ii)Median Range

It is another type of measurement for central tendency which is defined as Median. It generates when the middle number is listed from less to greatest. There may be an even number which has to position in the middle if there are 3 groups.  For this occurrence, it needs to do the average of two numbers of values (Peyser et al. 2018, p. 10). If there are 4 groups then, the average is generated for three numbers of values. On those procedures, the first step is to make sure about the problems and find why those are in the problems.

B. (i) Recommended Products for each of three groups

There are three types of device involves in Segment A, B, and C. These are based on their capacity and price.

For Low, High and Medium Capacity

Module class

€/Wp

Trend since April 2019

Trend since August 2019

Description

High Efficiency

0.35

0.0%

0.0%

Crystalline Modules above 290 Wp and above n-type, PERC, HJT or their combination

Medium Capacity

0.36

+2.9%

0.0%

The module type is black sheets and has black frames also. It is rated between the power 200 and 320 Wp

Low Capacity

0.20

0.0%

+11.1%

Insolvency of goods, Factory, using the low output which is also based on the crystalline. Limited product and no warranty

Table 2: Description of Low, High and Medium Capacity

(Source: Huang et al. 2016, p. 2223)

Here the recommended segment is B which is Medium Capacity. It is recommended because the medium capacity has 0.36 wp and also the power is between 200 to 320 Wp (Huang et al. 2016, p. 2223). The module is the combination of black frames and black sheets which is essential for controlling Smart Home.

 

(ii)The probability of for online usage for a new household

The probability is based on the relative frequency. Another type of probability is the estimation of the subjective method which is based on a person’s experience. It needs to estimates the function which is used for the probability which is successful in 40% of the process (Wei et al. 2019, p. 92). The estimation of subjective methods is depended upon the probability. There is another approach that is possible in different cases. The approach is often very simple after getting the visualization.

Part 3: Proposal

3.1 Introduction

The research that is being proposed is on the assessment of the 3D printer usage by the consumers and the technology acquired and accepted in the industry. The research will enlighten the 3D printer manufacturing company an idea of the market and approach that is required for spreading the small or micro-sized business in the new field. The company has a lack of knowledge in this field and it is required for accomplishing its objectives. The research will be helpful not only for the company but also the industry. The newly established industry is required to be spread and the work done in this industry has requirements of this technology.

 

3.2 Proposed Research

The prime concern of the research is to assess the market of the 3D printer and help the manufacturer to expand its business. A manufacturer of 3D printers wants to expand its market into small and micro-sized businesses (Ambrosi and Pumera, 2016, p. 2755). The businesses have a lack of knowledge about the technology, its usage, the process of manufacturing, and most importantly, the market of the technology. The research will be helpful to make the business successful if it helps in assessing the market and increasing the knowledge of the business entities. This comes to the assessment of the consumer’s attitude towards this particular technology (Zhu et al. 2016, p. 110). Another aspect of the research is to acquire methods to provide knowledge of the technology, its usage, and manufacturing method to small businesses. The research also assesses the possibility of building the infrastructure to acquire the technology is also a subject to be assessed by the researcher.

 

3.3 Research Findings

3D printing deals with the manufacturing or creating three dimensional solid objects from a digital image. The method of creating the object is to construct successive layers of the plastic material used for 3D printing to the point when the object is created completely. This helps in creating complex shapes of different things that are difficult to create manually. The programming of the printer is also quite simpler than any other manufacturing tools. The material used in the printing is strong enough to build parts of machinery, so this will also help in industrial jobs. Hence, the technology can be acquired for industrial purposes.

 

Findings from surveys

There have been conducted surveys to assess the usage of 3D printing in their daily lives. The survey conducted in the designing field has acquired the following data. The question asked if the technology is being used for official purposes. The construction and designing field disclosed that to implement and understanding the detailed designs of the construction is very easy with the help of the technology.

There have been surveys in the automobile industry, civil engineering, and the medical field and the results of the surveys provide knowledge of the usage. In the automobile industry, the car designs are being made with 3D printers than in the 2D software. The manufacturers say that it is easy to make the subordinates understand the designs with the help of the 3D design. Similarly in the medical and engineering field the designing and testing of the parts of machinery are benefited from 3D printing technology.

Information acquired from secondary research

There have been researches before on 3D printing in the context of its usefulness. The research suggested that the material used for printing is a strong polymer, so it will help to create a strong structure. Hence, in designing, it is useful for assessing not only the structure but also the density of the real thing. This can be programmed by the software allocated with the printer. This allows the applicability of 3D printing.

The researchers also suggest that the 3D printer can also generate in manufacturing the parts of machinery in small machines. Hence, the application of technology is enhanced in the industrial field. This is more effective in small businesses where small machinery is used. This is exactly what this present research is desired to find out. Hence, from the secondary research, the present research is justified.

 

3.4 Methods and Approaches

The research wheel has been acquired for the research and the approaches are inductive and deductive approaches can be appropriate for the research.

The wheel is the pattern in which the research is conducted. The research starts with a theory or literature cited. The deductions are made from some previous research and together with the objective of taking the research further and acquiring some benefit from the results. The literature cited had generated some questions or hypotheses on which the present research has been done (Zhang et al. 2016, p. 1703).

Figure 1: Research Wheel

(Source: Godoi et al. 2016, p. 50)

The methods that have been acquired for the research are either inductive or deductive which will be discussed later. The conduction of the research includes data collection and observations. The empirical observation is further proposed and the data is analyzed. This leads to a new theory that is added with the previous and generates scope for more research.

The methods that can be acquired for the research are either inductive or deductive. The inductive approach is to conduct research on the basis of observations and mixing it up with the theory to present a conclusion. The deductive approach is the scientific method of conducting surveys and interviews to acquire raw data. The data is then analyzed and a conclusion is acquired (Vukicevic et al. 2016, p. 180).

In this research, the deductive method is chosen because it requires acquiring raw data from the field and the analysis is to be made must be on current data. There are surveys and interviews acquired and the secondary research analysis is made.

 

3.5 Summary

Summarizing the whole proposal it is to be mentioned that the research is conducted with the motive of assessing the usage of 3D printing and the acceptance of the technology for industrial purposes. The findings have been acquired from the surveys and interviews and a deductive approach is proposed in the research. In the sections above the proposal, findings and methods of the research are discussed. The usage of a 3D printer is justified in daily life and industry and a possible market is also assessed. The research will be beneficial for the business that is to be expanded in the market.

Conclusion

The assignment has depicted some useful results. The first part established a unique point by analyzing the data on consumer usage. The needs and requirements of the customers of the motor vehicle company are assessed. The second part has depicted the consumer usage from the data by the analysis of standard deviation and upper quartile. The third part has given a proposal to conduct research for the betterment of the knowledge of the company on 3D printing. The research is conducted in the deductive method and standard research wheel. Based on the report the marketing plan will be acquired by the company. In the last part, a proposal to conduct research on the usage and acquisition of 3D printers by the consumers is provided. The research methodology, aspects and learning outcomes of the proposal are provided.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

References

Ambrosi, A. and Pumera, M., 2016. 3D-printing technologies for electrochemical applications. Chemical Society Reviews, 45(10), pp.2740-2755.

Godoi, F.C., Prakash, S. and Bhandari, B.R., 2016. 3d printing technologies applied for food design: Status and prospects. Journal of Food Engineering, 179, pp.44-54.

Krishen, A.S., Raschke, R.L., Close, A.G. and Kachroo, P., 2017. A power-responsibility equilibrium framework for fairness: Understanding consumers' implicit privacy concerns for location-based services. Journal of Business Research, 73, pp.20-29.
Niu, Y. and Wang, C.L., 2016. Revised unique selling proposition: scale development, validation, and application. Journal of Promotion Management, 22(6), pp.874-896.
Sebald, A.K. and Jacob, F., 2018. Help welcome or not: Understanding consumer shopping motivation in curated fashion retailing. Journal of Retailing and Consumer Services, 40, pp.188-203.
Erevelles, S., Fukawa, N. and Swayne, L., 2016. Big Data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), pp.897-904.
Yurova, Y., Rippé, C.B., Weisfeld-Spolter, S., Sussan, F. and Arndt, A., 2017. Not all adaptive selling to omni-consumers is influential: The moderating effect of product type. Journal of Retailing and Consumer Services, 34, pp.271-277.
Zhang, B., He, X., Ouyang, F., Gu, D., Dong, Y., Zhang, L., Mo, X., Huang, W., Tian, J. and Zhang, S., 2017. Radiomic machine-learning classifiers for prognostic biomarkers of advanced nasopharyngeal carcinoma. Cancer letters, 403, pp.21-27.
Wei, G., Yaqi, R., Ningfu, W. and Xuwei, H., 2019. N-terminal prohormone B-type natriuretic peptide and cardiovascular risk in stable coronary artery disease: a meta-analysis of nine prospective studies. Reviews in cardiovascular medicine, 14(2-4), pp.92-98.
López, N., Erwin, C., Binder, M. and Chavez, M.J., 2018. Making the invisible visible: Advancing quantitative methods in higher education using critical race theory and intersectionality. Race Ethnicity and Education, 21(2), pp.180-207.
Peyser, T.A., Balo, A.K., Buckingham, B.A., Hirsch, I.B. and Garcia, A., 2018. Glycemic variability percentage: a novel method for assessing glycemic variability from continuous glucose monitor data. Diabetes technology & therapeutics, 20(1), pp.6-16.
Huang, Y., Wang, Z., Liao, B., Liang, J.Y., Zhou, L.Y., Wang, F., Li, W., Liu, J.Y., Xie, X.Y., Lu, M.D. and Liu, G.J., 2016. Assessment of liver fibrosis in chronic hepatitis B using acoustic structure quantification: quantitative morphological ultrasound. European radiology, 26(7), pp.2344-2351.

Vukicevic, M., Mosadegh, B., Min, J.K. and Little, S.H., 2017. Cardiac 3D printing and its future directions. JACC: Cardiovascular Imaging, 10(2), pp.171-184.

Zhang, Q., Zhang, F., Medarametla, S.P., Li, H., Zhou, C. and Lin, D., 2016. 3D printing of graphene aerogels. Small, 12(13), pp.1702-1708.

Zhu, W., Ma, X., Gou, M., Mei, D., Zhang, K. and Chen, S., 2016. 3D printing of functional biomaterials for tissue engineering. Current opinion in biotechnology, 40, pp.103-112.

 

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