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Prepare a thesis on the use3D in construction and Project Engineering management.

Variables That Might Influence the Acceptance of 3D Printing for Construction and Management

Innovations in printers, especially 3D printers have had several valuable impacts on the industry (Wu, Wang & Wang, 2016). Application of 3D printers in construction and management faces several challenges. Some of the research problems have been discussed and detailed out in the literature review. Analysis of research questions have been undertaken here to analyse the potential impact of 3D printers in constructions with analysis of future scope and challenges.  

The inquiries of this examination are intended to analyse the requirements presented through previous chapter. The scope of this analysis contains to address the exploration issues characterized in the past section for analysis of 3D printing impact on the construction industry (Gosselin et al. 2016).

Q1: What is the current perception of the 3D printing in construction industry?

One of the real finding of the scholarly analysis revealed through the papers that address the 3D printing technology design provides that there is no experimentally information accumulation about the impression of 3D in construction. Most of the flow coordinated in 3D printing design endeavors to apply itself in construction and management is in accordance to the researcher’s  observation and assessment. In any case, there are not very many gathered and analytical information attempting to concentrate and feature the fundamental issues that the 3D printing confront primary issues by improving the present undertaking design systems.

To conduct this inquiry, a review has to be undertaken construction and management. To arrive at appropriate results is to be able to quantify the present impression of the undertaking 3D printing in term of the need in construction and management.

H1: Most of the construction engineers perceive 3D printing is importance in construction industry.

Q2: What are the variables that might influence the acknowledgment of having 3D printing techniques to be applied across construction industry?

Such inquiry may be replied by proposing the accompanying inquiries and planning the correct speculations to answer them.

Q2a: How would the size of the organization determine the agreeableness of the 3D printing?

In this inquiry the extent of the organization where the 3D printing stakeholder have encountered their endeavor design experience; might influence whether they would have a positive discernment toward having the techniques connected with construction and management.

H2a: The span of business measure impacts the impression of the 3D printer stakeholder on the construction.

Q2b: Do 3D printers stakeholders see more positive aspects recognition about application of the endeavor to construction engineering practices and systems than those with less or no 3D printing  approaches?

The Size of the Organization Impact on 3D Printing in Construction

H2b: The ability of 3D printing to impact on the construction and management.

Q2c: Does more reliance of 3D printing on the present endeavor on construction contrarily influence her/his acknowledgment impression of the 3D printing?

H2c: The reliance of big business on 3D printers in construction and management big business design structures impacts the construction and management.

Q3: What are the 3D printing Motivators?

There are present diverse motivations to adopt 3 D printers in construction; the significant reason is the progress and technological adaptations in businesses. In order to construct a logical rundown of motivators various ones proposed by different scholars has to be incorporated into the system plan as primary undertaking design motivators. Some of the advantages of motivators are highlighted.

  1. 3D printing responsiveness to business and IT changes.

H3a: A large portion of enterprises in the field of construction are undertaking design 3D printing framework to be more receptive to the business and IT changes.

  1. The disruptive technologies as cloud and versatile figuring challenges.

H3b: A large portion of the construction industry ought to be more adaptive to the disruptive technologies.

  1. Construction engineering constant change and criticism.

H3c: A large portion of the construction engineers stresses on the need of having nonstop changes and input into the system.

Q4: What are the 3D printing Enablers?

3D printing enablers includes the strategies that can impact construction and management. 3D printing has various principles and framework that help develop perspective of application on construction and management. It may they are still so potential to be center standards to grow such assessment structure.

  1. The most noteworthy need is to customer satisfaction by means of through right on time and consistent conveyance of profitable.

H4a1: The vast majority of the 3D printing agree that consumer loyalty through early conveyance is an empowering agent to have a coordinated construction and management.

  1. Deliver working undertaking construction, from a long time to two or three months, with an inclination to the shorter time lines.

H4a2: A large portion of the 3D printing accept that frequent delivery is an empowering influence on construction and management.

  1. 4. Construction and management stakeholders (customers and construction engineers) must cooperate every day all through the task.

H4a3: The greater part of the 3D printers arise through that cooperation between stakeholders is an empowering agent to have an effective construction engineering.

In this section the examination questions required with address the exploration issue; and appropriately by planning the required speculations to test and answer these inquiries. To outwardly abridge the examination inquiries and theories we built up the accompanying outline to delineate the connections between the exploration issue, inquiries, and speculations.

A questionnaire was designed keeping in mind the end goal to be circulated to the examination populace test. To encourage a simple correspondence with the members the online questionnaire tool from qualtrics.com was adopted (Appendix 1).

The objective populace was targeted to construction engineers, from the both genders, 18 years of age or more, with no less than 1 years of involvement in construction and management.

The Ability of 3D Printing to Impact on Construction and Management

The focused on test has been set to achieve 160+ from the above characterized target populace, before the finish of the overview opening period (20 January 2018 till 15 April 2018) to get total contributing 149 participants.

Keeping in mind the end goal to guarantee exact aftereffects of the survey, a watchful segment procedure of the questionnaire participants needs to occur. Such cautious determination has been accomplished by welcoming invitees who have demonstrated profiles that match the objective populace criteria; this has been finished by auditing the profiles of the invitees on LinkedIn as a standout amongst the most solid and endorsed proficient person to person communication media. In the wake of evaluating the profile of the potential invitee and having a positive after-effect of the profile checking process, a welcome message has been sent to the participants clarifying the examination and the survey goals and desires. The participants in the study was provide with the questionnaire and details regarding the test was explained to them. All inputs regarding the study was explained to them in a detailed manner so as to arrive at appropriate answers form the study procedure.

The rest of the parts of the examination philosophies, which is. the information investigation and speculations testing, the system approval, and the record configuration are clarified and itemized in the accompanying parts (Lim  et al., 2012). The questionnaire covered qualitative as well as quantitative data. Qualitative data was analysed in a descriptive manner whereas quantitative data collected was analysed using Chi- square Test.    

In this part, all the information gathered utilizing the online survey with a specific end goal to test and approve the proposed theories.

Initially, there will be some measurable examination of the assembled information with a specific end goal to display a portrayal of the example population; the factual investigation incorporates depicting the: endeavor sizes, the members' parts, the systems utilized as a part of their undertakings, and their involvement in term of dexterous procedures (Mueller et al., 2014). 

At that point, we furthermore show an inferential measurable examination of the information keeping in mind the end goal to make deductions about the populace in light of the contemplated test. This chapter of analysis includes qualitative as well as quantitative data collected from the questionnaire of the study.

In order to arrive at analysis pertaining to the study more data about the assembled and investigated information has to be understood (Bos et al., 2016). The accompanying descriptive analysis regarding primary data that is collected will illustrate some critical points related to the study.

The Reliance of Business on 3D Printers in Construction and Management Big Business Design Structures Impacts the Construction and Management

The extent of the size of the construction enterprises participants are described, the below  diagram demonstrates that most of the members have worked for are from large enterprises.

While analysing roles of participants who provided their feedback, most of them were believed to be designers using 3D printers, as designing consists of most integral aspect.

While analysing participants dependence, it was revealed that most participants makes use of 3D while making their construction designs. Most of the participants were between 5-12 years working with 3D printing techniques in constructions.

The research hypothesizes has made analysis of theories so as to answer the research questions; these speculations ought to be tried and approved utilizing diverse factual techniques. Here for the purpose of analysis, Chai-Square Test, and the Residual Computation in order to interpret the result of the Chi-Square tests has been utilized..

Perception Theory: H1

In this part we examine the observation theory that tends to the endeavor construction stakeholders recognition about applying the 3D printing procedures on the undertaking engineering.

This speculation theorizes that the vast majority of the undertaking engineering partners see decidedly applying the 3D printing techniques on the endeavor design:

H1: The majority of the undertaking engineers see 3D printing significance in big business design; (where most >= 65%).

To test this speculation, planning the invalid and the elective theories as following:

H1-0: Under 65% of the construction stakeholders design partners see emphatically applying the 3D printing approaches on the designing.

H1-alt: Over 65% of the construction stakeholders emphatically applying the 3D printing approaches on the designing.

Utilizing single populace extent one followed test on the information gathered, the following results is arrived at:

N

α

π

Count of Yes Answers

Count of No Answers

p-value

149

0.05

0.65

119

19

0.01


As per the consequences of the examination and the little p-value, it is best to dismiss H1-0 and state with certainty that the vast majority of the undertaking engineers see a significance to have greater dexterity in the construction design.

Such positive outcome will support the center research question and goal of this examination by demonstrating that the undertaking planners concede to applying the procedures in the endeavor engineering practices and structures. Later speculations dialog will investigate and detail on and to which levels venture designers point the arrangement between the 3D printing and the construction engineering.

Influence Speculations: H2

In this part testing and approve the speculations that address contemplating if there are factors that influence the acknowledgment of having the 3D printing techniques to be connected to the construction design (Petrovic et al., 2011). The theories address the impact of the enterprise sizes, the impact of the 3D printing awareness, and the impact of the systems reliance.

The Impact of Enterprise Size: One of the hypothesized impacts in this examination is the impact of the enterprise size on the acknowledgment of the construction engineering.

The theory proposed in this exploration with respect to this subject is:

H2a: The measure of big business estimate impacts the acknowledgment view of the undertaking engineering partners of the dexterous venture design.

In order to test this hypothesis, null and the alternative hypotheses is constructed as following:

H2a-0: The enterprise size and the acknowledgment view of the construction enterprise stakeholders of the 3D printing is independent.

H2b-alt: The enterprise size and the acknowledgment view of the construction enterprise stakeholders of the 3D printing are dependent.

Keeping in mind the end goal to test the reliance relationship between two downright factors the Chi-Square test is applied.

As needs be, we set up the accompanying possibility tables, and apply a Chi-Square to test them.

Observed

Small

Mid

Large

Total

Negative Perception

6.00

11.00

17.00

34.00

Not Positive Not Negative

12.00

4.00

17.00

33.00

Positive Perception

12.00

52.00

86.00

150.00

Total

30.00

67.00

120.00

217.00

Table 2 - H2a Observed Values

Expected

Small

Mid

Large

Total

Negative Perception

 6

 11

 17

34.00

Not Positive Not Negative

 3

 14

 16

33.00

Positive Perception

 21

 42

 87

150.00

Total

30.00

67

120.00

217.00

Table 3 - H2a Expected Values

Conducting the Chi-Square test, resultant p-value = 0.00; which is extremely small compared to the significance level (0.05). Hence, it can be considered safely that there is sufficient evidence to reject the null hypothesis H2a-0, and to confirm that the 3D printing technologies applications and the organizational size are interrelated and not independent.

While applying Chi-Square result of the independency test, it was understood that there is significantly relation between the organizational size and the 3D printing technologies acceptance. But in order to interpret the results of the Chi-Square analysis by calculating the standardized residuals, as per the following formula:

Where O: Observed Values, E: Expected Values

Accordingly, the following table of the standardized residual is arrived at:

Standardized Residual

Small

Mid

Large

Negative Perception

-0.004079085

0.0

0.0

Not Positive Not Negative

+5.196152423

-2.672612419

0.25

Positive Perception

-1.963961012

+1.5430335

-0.107211253

Table 4 - H2a Standardized Residuals

An standardized residual that has absolute value that surpasses around 2 when there are couple of cells or around 3 when there are numerous phones shows absence of attack of Ho. When cells' standardized residual value is more noteworthy/not exactly +/ - 2, relating classifications are viewed as real supporters of the essentialness of the reliance affiliation. For the current state, the (red featured) cell of the "Not Positive Not Negative" with the "Little" exhibits the significant commitment to the relationship between the 3D printing innovations acknowledgment and the extent of the authoritative unit. It can be expressed that the reliance affiliation demonstrated utilizing the Chi-Square test is particularly material when the undertaking size is little, as the venture engineering partners have a tendency to have no inclination toward the 3D printing advancements and reply with the appropriate response "Not Positive Not Negative".

It is very critical to see that this outcome underpins our past about the positive view of the undertaking engineering partner, as we understood that the hierarchical size influences the members who answered with unbiased recognition "Not Positive Not Negative"; realizing that these member's answers are rejected from the measurements trial of the observation question bolsters our outcomes as it is identified with the ordinarily dispersed reactions, i.e. the non-influenced members.

Do 3D printing techniques-aware enterprise architecture stakeholders perceive more positive perception about accepting the 3D printing techniques methodologies application on the enterprise architecture practices and frameworks compared to those with less or no 3D printing techniques methodologies awareness?

H2b: The awareness of the agility methodologies influences the acceptance perception of the 3D printing technologies for the enterprise architects.

To test this hypothesis, formulating the null and the alternative hypotheses has to be attempted as following:

H2b-0: The awareness of the agility methodologies and the acceptance perception of the enterprise architecture stakeholders of the 3D printing technologies are independent.

H2b-alt: The awareness of the agility methodologies and the acceptance perception of the enterprise architecture stakeholders of the 3D printing technologies are dependent.

In order to test the dependency association between two categorical variables we apply the Chi-Square test.

Accordingly, we prepare the following contingency tables, and apply a Chi-Square to test them.

Observed

 1 to 3

 4 to 10

 10 to 20

 > 20

 No

Total

 Negative Perception

7.00

5.00

2.00

-

2.00

16.00

 Not Positive Not Negative

4.00

3.00

1.00

-

11.00

19.00

 Positive Perception

34.00

40.00

14.00

-

23.00

121.00

Total

45.00

48.00

27.00

36.00

149.00

Table 5 - H2b Observed Values

Expected

 1 to 3

 4 to 10

 10 to 20

 > 20

 No

Total

 Negative Perception

4.62

4.92

2.77

-

3.69

16.00

 Not Positive Not Negative

5.48

5.85

3.29

-

4.38

19.00

 Positive Perception

34.90

37.23

20.94

-

27.92

121.00

Total

45.00

48.00

27.00

36.00

149.00

Table 6 - H2b Expected Values

Applying the Chi-Square test, we conclude that the p-value = 0.0041965; which is a smaller enough than the considered significance level (0.05); therefore, we can safely state that there is sufficient evidence to reject the null hypothesis H2b-0, and to confirm that the 3D printing technologies acceptance and the agility methodology awareness are interrelated and not independent.

Interpreting the Chi-Square Results: Standardized Residual Calculation

As per the Chi-Square result of the independency test, it turned out that there is significantly an association between the agility awareness of the enterprise architecture stakeholder and the 3D printing technologies acceptance; to interpret the results of the Chi-Square analysis we will apply the same method of calculating the standardized residuals as per (explained in the previous hypothesis); accordingly, we can get the following table of the standardized residual:

Standardized Residuals

 1 to 3

 4 to 10

 10 to 20

 > 20

 No

 Negative Perception

+0.93

-0.11

+0.1

-0.88

-0.98

 Not Positive Not Negative

-0.657

-1.3

-0.82

-1.62

+2.92

 Positive Perception

-0.04

+0.58

+0.3

0.96

-0.84

Table 7 - H2b Standardized Residuals

We  can see the (red highlighted) cell of the "Not Positive Not Negative" with the "No Agility Experience" presents the major contribution to the association between the 3D printing technologies acceptance and the awareness of the agility methodologies, and we can state that association proved by Chi-Square test is specifically applicable when the organization enterprise architecture stakeholders' don’t have agility experience, and they tend to have no preference toward the 3D printing technologies and answer with "No Positive No Negative".

It is highly important to notice that this result supports our previous about the positive perception of the enterprise architecture stakeholder, as we realized that the agility methodologies awareness affects the participants who replied with neutral perception "Not Positive Not Negative"; knowing that these participant's replies are excluded from the statistics test of the perception question supports our results as it is related to the normally distributed responses, i.e. the non-affected participants.

Does more dependency of the enterprise architects on the current enterprise architecture frameworks negatively affect her/his acceptance perception of an 3D printing technologies?

H2c: The dependency of enterprise architect on enterprise architecture frameworks influences the acceptance perception of the 3D printing technologies.

In order to test this hypothesis, we formulate the null and the alternative hypotheses as following:

H2c-0: The dependency of enterprise architect on enterprise architecture frameworks and the acceptance perception of the enterprise architecture stakeholders of the 3D printing technologies are independent.

H2c-alt: The dependency of enterprise architect on EA frameworks and the acceptance perception of the enterprise architecture stakeholders of the 3D printing technologies are dependent.

In order to test the dependency association between two categorical variables we apply the Chi-Square test. Accordingly, we prepare the following contingency tables, and apply a Chi-Square to test them.

Observed

 All

 Guideline

 Initiate

 Docs

 Never

Total

 Negative Perception

 4.00

 8.00

 4.00

 -   

 16.00

 Not Positive Not Negative

 7.00

 10.00

 1.00

 1.00

 19.00

 Positive Perception

 43.00

 26.00

 24.00

 28.00

 121.00

Total

 54.00

 44.00

 29.00

 29.00

 149.00

Table 8 - H2c Observed Values

Expected

 All

 Guideline

 Initiate

 Docs

 Never

Total

 Negative Perception

 4.62

 4.92

 2.77

 3.69

 16.00

 Not Positive Not Negative

 5.48

 5.85

 3.29

 4.38

 19.00

 Positive Perception

 34.90

 37.23

 20.94

 27.92

 121.00

Total

 54.00

 44.00

 29.00

 29.00

 149.00

Table 9 - H2c Expected Values


Applying the Chi-Square test, we conclude that the p-value = 0.0122477; which is a smaller enough than the considered significance level (0.05); therefore, we can safely state that there is sufficient evidence to reject the null hypothesis H0, and to confirm that the 3D printing technologies acceptance and the enterprise architects' dependency on the frameworks are interrelated and not independent.

Interpreting the Chi-Square Results: Standardized Residual Calculation

As per the Chi-Square result of the independency test, it turned out that there is significantly an association between the dependency on the enterprise architecture frameworks and the 3D printing technologies acceptance; to interpret the results of the Chi-Square analysis we will apply the same method of calculating the standardized residuals as per (explained in the previous hypothesis); accordingly, we can get the following table of the standardized residual:

Standardized Residuals

 All

 Guideline

 Initiate

 Docs

 Negative Perception

+0.98

-0.32

+0.68

-0.96

 Not Positive Not Negative

+2.38

-1.15

+0.5

-0.09

 Positive Perception

-1.3

+0.57

-0.45

+0.39

Table 10 - H2c Standardized Residuals

We  can see the (red highlighted) cell of the "Not Positive Not Negative" with the "All" presents the major contribution to the association between the 3D printing technologies acceptance and the dependency on the enterprise architecture frameworks, and we can state that association proved by Chi-Square test is specifically applicable when the enterprise architects depend completely on the enterprise architecture frameworks, and they tend to have no preference toward the 3D printing technologies and they answer with "No Positive No Negative".

It is highly important to notice that this result supports our previous about the positive perception of the enterprise architecture stakeholder, as we realized that the framework dependency affects the participants who replied with neutral perception "Not Positive Not Negative"; knowing that these participant's replies are excluded from the statistics test of the perception question supports our results as it is related to the normally distributed responses, i.e. the non-affected participants.

3D printing technologies Application Hypotheses: H3, H4

In this part of the hypotheses testing we are going to test the hypotheses proposed to formulate the foundational framework between the enterprise architecture and 3D printing techniques methodologies; as per the questions formulation in chapter 3 and the literature review in chapter 4 the framework includes three forces that affect the application of the 3D printing technologies. The hypotheses of each one of these forces will studied and validated in the next sections.

Motivators Hypotheses: H3a

The first force of the foundational framework of application of the 3D printing techniques methodologies on the enterprise architecture is the motivators; according to our literature review we propose seven motivators, each one of them will be studied alone using a single population proportion one tailed test.

3D Printing Application to Changes in Construction Business.

This hypothesis suggests that having more responsiveness 3D printing to the construction business. These businesses currently might be able to potentially motivate to adopt more 3D printing technologies while making their various construction related drawings. Therefore, the following hypothesis to study this question can be stated comfortably:

H3a: Most of the enterprise architects agree that enterprise architecture should be more responsive to the business and IT changes; (where most >= 65%).

To test this hypothesis, we formulate the null and the alternative hypotheses as following:

H3a-0: less than 65% of the enterprise architecture stakeholders agree that enterprise architecture should be more responsive to the business and IT changes. 

H3a-alt: more than 65% of the enterprise architecture stakeholders agree that enterprise architecture should be more responsive to the business and IT changes. 

Using single population proportion one tailed test on the data collected, we get the following:

N

α

π

Count of Yes Answers

Count of No Answers

p-value

149

0.05

0.65

120

11

0.02959

Table 11 - H3a Statistics Test

According to this analysis, we can state with confidence that there is a sufficient evidence to say that the 3D printing responsiveness to the construction business is a motivator to have an 3D printing technologies. Due to the various benefits derived from it thereof.

Disruptive Technologies Challenges

This hypothesis suggests that having more disruptive technologies adaptable enterprise architecture might be a potential motivator to adopt the 3D printing technologies. Accordingly, we can state the following hypothesis to study this question:

H3b: Most of the construction engineers agree that 3D printing should be more adaptable to the construction business; (where most >= 65%).

In order to test this hypothesis, formulation of the null and the alternative hypotheses as following:

H3b-0: less than 65% of the enterprise architecture stakeholders agree that enterprise architecture should be more adaptable to the disruptive technologies challenges. 

H3b-alt: more than 65% of the enterprise architecture stakeholders agree that enterprise architecture should be more adaptable to the disruptive technologies challenges. 

Using single population proportion one tailed test on the data collected, we get the following: 

N

α

π

Count of Yes Answers

Count of No Answers

p-value

149

0.05

0.65

120

22

0.02959

Table 13 - H3c Statistics Test

According to this analysis, it can be stated that with confidence that there is a sufficient evidence to say that construction engineers prefer and agree that having 3D printing frameworks has capabilities to deliver more changes. There are ready deliverables that can show the construction business changes after the enterprise architecture practices is a motivator to have a 3D printing technologies.

The EA Stakeholders’ Communication and Collaboration

This hypothesis suggests that having more communicative and collaborative 3D printing technologies can potentially motivate to adopt the 3D printing technologies. Therefore accordingly, the following hypothesis to study this question can easily be stated as;

EA Continuous Improvement and Feedback

This hypothesis suggests that having more communicative and collaborative enterprise architecture might be a potential motivator to adopt the 3D printing technologies. Accordingly, we can state the following hypothesis to study this question:

Hc: Most of the construction engineers agree on the necessity of having continuous improvement and feedback during and post application of 3D printing technologies (where most >= 65%).

In order to test this hypothesis, the following formulation of the null and the alternative hypotheses as following can be constructed:

H3c-0: less than 65% of the construction engineers stakeholders agree that 3D printing should have more continuous improvement and feedback. 

H3c-alt: more than 65% of the construction engineers stakeholders agree that 3D printing should have more continuous improvement and feedback. 

Using single population proportion one tailed test on the data collected, we get the following: 

N

α

π

Count of Yes Answers

Count of No Answers

p-value

149

0.05

0.65

123

19

0.00795

Table 15 - H3e Statistics Test

According to this analysis, we can state with confidence that there is a sufficient evidence to say that enterprise architects agree that having continuous improvement and feedback during and after the EA practices is a motivator to have a 3D printing technologies.

3D printing techniques Schwarzites Principles

The main source adopted to extract the agility enablers is the 3D printing techniques Schwarzites Principles that consists of four values and twelve principle; according to, this research will consider studying the perspective of the enterprise architects of the application of these twelve principles on the enterprise architecture as enablers, each one of these twelve principles will studied using its specific hypothesis testing.

H4a1: Most of the enterprise architects agree that customer satisfaction through early delivery is an enabler to have an 3D printing technologies; (where most >= 65%).

To test this hypothesis, we formulate the null and the alternative hypotheses as following:

H4a1-0: less than 65% of the enterprise architecture stakeholders agree that the early delivery might be an enabler for an 3D printing technologies. 

H4a1-alt: more than 65% of the enterprise architecture stakeholders agree that the early delivery might be an enabler for an 3D printing technologies. 

Using single population proportion one tailed test on the data collected, we get the following: 

N

α

π

Count of Yes Answers

Count of No Answers

p-value

149

0.05

0.65

139

5

9.6228E-08

Table 18 – H4a1 Statistics Test

According to this analysis, it can be stated with confidence that there is a sufficient evidence to say that customer satisfaction through early delivery is a 3D printing technologies enabler.

H4a2: Most of the construction engineers agree that welcoming changing requirements is an enabler to have an 3D printing technologies; (where most >= 65%).

To test this hypothesis, we formulate the null and the alternative hypotheses as following:

H4a2-0: less than 65% of the enterprise architecture stakeholders agree that welcoming changes might be an enabler for an 3D printing technologies. 

H4a2-alt: more than 65% of the enterprise architecture stakeholders agree that welcoming changes might be an enabler for an 3D printing technologies. 

Using single population proportion one tailed test on the data collected, we get the following: 

N

α

π

Count of Yes Answers

Count of No Answers

p-value

149

0.05

0.65

126

13

0.00167

Table 19 - H4a2 Statistics Test

As per this analysis, it can be stated with confidence that there is a sufficient evidence to say that welcoming changing requirements is an enabler to have an 3D printing technologies.

H4a3: Most of the construction engineers agree that frequent delivery is an enabler to have a 3D printing technologies; (where most >= 65%).

To test this hypothesis, we formulate the null and the alternative hypotheses as following:

H4a3-0: less than 65% of the construction engineers stakeholders agree that frequent delivery might be an enabler for an 3D printing technologies. 

H4a3-alt: more than 65% of the enterprise architecture stakeholders agree that frequent delivery might be an enabler for a 3D printing technologies. 

Using single population proportion one tailed test on the data collected, we get the following: 

N

α

π

Count of Yes Answers

Count of No Answers

p-value

149

0.05

0.65

126

22

0.00167

Table 20 - H4a3 Statistics Test

According to this analysis, we can state with confidence that there is a sufficient evidence to say that frequent delivery is an enabler to have a 3D printing technologies.

H4a4: Most of the construction engineers agree that collaboration between stakeholders is an enabler to have a 3D printing technologies; (where most >= 65%).

To test this hypothesis, we formulate the null and the alternative hypotheses as following:

H4a4-0: less than 65% of the enterprise architecture stakeholders agree that collaboration between stakeholders might be an enabler for a 3D printing technologies. 

H4a4-alt: more than 65% of the enterprise architecture stakeholders agree that collaboration between stakeholders might be an enabler for a 3D printing technologies. 

Using single population proportion one tailed test on the data collected, we get the following:

N

α

π

Count of Yes Answers

Count of No Answers

p-value

149

0.05

0.65

117

17

0.08

Table 21 - H4a3 Statistics Test

According to this analysis, we can state with confidence that there is a sufficient evidence to say that collaboration between stakeholders is an enabler to have an 3D printing technologies.

According to the data analysis and the results concluded in the previous sections it can be understood that the proposed framework according to the hypotheses testing results by excluding the non-proved hypotheses and retaining the proved ones (Bogue, 2013). As per analysis it can be understood that the following hypotheses validation illustration, and next to it the validated and final version of the framework.

Conclusions

In this chapter it was described that the conclusions of the research based on the results of the data analysis and we introduce the deliverables of this research work. The research main objectives are to propose a foundational framework for application of the 3D Printing methodologies on the construction engineer. An evaluation index for the 3D Printing framework,  supports the stated proposals by evaluating the construction business stakeholders' perception of accepting such application and the influencers that affect such perception.

It is remarkably debatable within the domain of the 3D Printing to decide if the 3D Printing methodologies can be applied on the construction engineering or not. By having the 3D printing technologies becoming largely evaluated topic enhances the debate and deepen the conflict between the benefits and disadvantages of 3D printing technologies. Reviewing the academic literature review depicts not much previous work in assessing the perception of the construction business stakeholders about the topic. The research results show with significance that construction engineers perceive positively the application of the 3D Printing methodologies on the construction engineers. Therefore proven positive perception encourages more efforts and work to be dedicated in this field.

Such any other perceptions, many influencers are potential to be affecting the population under testing. As per the study conducted, it can be concluded that the construction engineering business’ stakeholders' perception is affected by the business size. The construction engineering dependency, and the 3D printing techniques methodologies awareness; can be critically be noticed that these influencers impact the participants that gave answers with neutral perception. "Not Positive Not Negative", knowing that these participants’ replies are excluded from the statistics test of the perception question supports the results as they related to the normally distributed responses.

The framework for the research undertaken further proposes that application of the 3D  methodologies on construction engineering has been a subject that has been centrally affected by the three forces, motivators, enablers and blockers. According to the research results can be concluded that the 3D printing technologies is motivated by the Business. Construction Engineering businesses which includes construction businesses. 3D Printing deliverables to reflect the business after the construction practice. The last motivator includes Clients Engagement with construction engineers includes, construction engineering business stakeholders’ communication along with collaborations. 3D Printing Continuous Improvement and Feedback along with 3D Printing Practical Experimentation of Deliverables. As per the data analysis it can be excluded that the Value Driven 3D Printing from the list of the 3D printing technologies motivators in construction engineering.

In term of the enablers, it can be proposed that the 3D printing techniques manifesto twelve principles as enablers for the 3D printing technologies in addition to the visualization and the service oriented architecture. As per the data analysis and the hypotheses testing it was proved that Visualization, the Service Oriented Architecture, Effectiveness Monitoring and Enhancement, Continuous Attention to Excellence, Working 3D Printing act as a Primary Measure of Progress, Motivation, Collaboration, Frequent Delivery, changing needs, and Early Delivery are significantly accepted enablers to have 3D printing technologies. The results of the data analysis excluded the Self-Organizing Teams, Simplicity, Sustainable Architecture Development and Constant Pace, and the Face to Face Conversation from the potential suggested enablers as their related hypotheses could not be proven significant enough to be included in the framework.

Although the research was carefully and thoughtfully prepared, however we still aware of its limitations. First, the sample size could have been larger and more than 149 construction engineering companies stakeholders, the larger the sample size the more accurate results the research would result.

Secondly, the time limitation was vital in scoping the work of the study, accordingly some potential further would have been done, some of these work is already known to us and proposed in the next section, i.e. the further work.

The examination principle expectations are the system of the 3D printing on construction engineering. There are numerous potential areas to keep working in this subject within deliverables. Firstly, it can be recommended that, the current 3D Printing frameworks in light of the proposed framework in this study and evaluating them according to the framework forces, i.e. motivators, enablers, and blockers. Secondly, the research focuses on answering the question of "What", and we believe that more work could have been done - given more time and population accessibility - to work on the question of "Why"; i.e. this research delivers an important result by accepting the proved and excluding the failed-to-be-proved motivators, enablers, and blockers of the proposed framework; however more work could have been done on describing and analyzing why the excluded or the failed-to-be-proved framework constituents have not been significantly accepted. Lastly, the index seen as a potential work in preparing a recommendations action map.

References

Bogue, R. (2013). 3D printing: the dawn of a new era in manufacturing?. Assembly Automation, 33(4), 307-311.

Bos, F., Wolfs, R., Ahmed, Z., & Salet, T. (2016). Additive manufacturing of concrete in construction: potentials and challenges of 3D concrete printing. Virtual and Physical Prototyping, 11(3), 209-225.

Gosselin, C., Duballet, R., Roux, P., Gaudillière, N., Dirrenberger, J., & Morel, P. (2016). Large-scale 3D printing of ultra-high performance concrete–a new processing route for architects and builders. Materials & Design, 100, 102-109.

Lim, S., Buswell, R. A., Le, T. T., Austin, S. A., Gibb, A. G., & Thorpe, T. (2012). Developments in construction-scale additive manufacturing processes. Automation in construction, 21, 262-268.

Mueller, S., Mohr, T., Guenther, K., Frohnhofen, J., & Baudisch, P. (2014, April). faBrickation: fast 3D printing of functional objects by integrating construction kit building blocks. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3827-3834). ACM.

Petrovic, V., Vicente Haro Gonzalez, J., Jordá Ferrando, O., Delgado Gordillo, J., Ramón Blasco Puchades, J., & Portolés Griñan, L. (2011). Additive layered manufacturing: sectors of industrial application shown through case studies. International Journal of Production Research, 49(4), 1061-1079.

Wu, P., Wang, J., & Wang, X. (2016). A critical review of the use of 3-D printing in the construction industry. Automation in Construction, 68, 21-31.

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