Prioritisation of drivers of sustainable additive manufacturing using best worst method

Figures & data

Figure 1. Methodological steps

Table 1. Previous studies on BWM application in Sustainability domain

Research Study	Focus
Rezaei et al. (2016)	Evaluating best supplier by considering sustainability criteria
Ahmadi, Kusi-Sarpong, and Rezaei (2017)	Evaluating social aspect of sustainability in supply chain domain.
Ahmad et al. (2017)	Analysed the external forces influencing the sustainability of oil and gas supply chain
Zhao, Guo, and Zhao (2018)	Analysed and ranked the eco industrial parks based on its benefits considering sustainability and circular economy in mind.
Malek and Desai (2019)	Analysed the barriers of SM for an Indian manufacturing firm.

Table 2. Consistency index (CI)

$a_{BW}$	1	2	3	4	5	6	7	8	9
CI value	0	0.4	1	1.63	2.3	3	3.75	4.47	5.23

Table 3. Drivers of sustainable additive manufacturing

Category	Driver	References
Material (M)	Optimum resources utilisation (M1)	Govindan, Diabat, and Shankar (2015); Bey, Hauschild, and McAloone (2013); Shankar, Kumar, and Kannan (2016)
	Reusing and recycling materials and packaging (M2)	Moktadir et al. (2018); Nordin, Ashari, and Hassan (2014)
	Less material wastage (M3)	Mani, Lyons, and Gupta (2014); Rahimifard et al. (2009)
Management and Stake Holders (M & SH)	Proper training and education (MSH1)	Bey, Hauschild, and McAloone (2013); Shankar, Kumar, and Kannan (2016); Vinodh, Ramesh, and Arun (2016)
	Incentives (MSH2)	Mittal and Sangwan (2014)
	Stake holder participation (MSH3)	Vinodh, Ramesh, and Arun (2016)
	Management support (MSH4)	Vinodh, Ramesh, and Arun (2016)
	Employee commitment towards sustainability (MSH5)	Vinodh, Ramesh, and Arun (2016)
Customer/ Supplier/ Competitor (CSC)	Customers’ expectations (CSC1)	Bey, Hauschild, and McAloone (2013); Shankar, Kumar, and Kannan (2016)
	Supplier commitment (CSC2)	Ageron, Gunasekaran, and Spalanzani (2012)
	Company image (CSC3)	Govindan, Diabat, and Shankar (2015); Searcy et al. (2012)
	Public pressure (CSC4)	Mittal and Sangwan (2014)
	Supply chain pressure (CSC5)	Mittal and Sangwan (2014)
	Competitor pressure towards greening (CSC6)	Moktadir et al. (2018); Ghazilla et al. (2015)
Collaboration and Trends (C & T)	Market trends (CT1)	Govindan, Diabat, and Shankar (2015); Searcy et al. (2012)
	Economic benefits (CT2)	Ghazilla et al. (2015); Nordin, Ashari, and Hassan (2014); Moktadir et al. (2018); Vinodh (2011)
	Collaboration between organisations (CT3)	Nordin, Ashari, and Hassan (2014); Moktadir et al. (2018)
	Long-term survival in market (CT4)	Nordin, Ashari, and Hassan (2014)
	Collaborative decision making (CT5)	Govindan, Diabat, and Shankar (2015); Vinodh, Ramesh, and Arun (2016)
Technology (T)	Green innovation (T1)	Bey, Hauschild, and McAloone (2013); Shankar, Kumar, and Kannan (2016);
	Energy conservation (T2)	Bey, Hauschild, and McAloone (2013); Shankar, Kumar, and Kannan (2016)
	Technology competence (T3)	Vinodh, Ramesh, and Arun (2016)
	Technology adaptability (T4)	Niaki, Torabi, and Nonino (2019)
	Time to develop new product (T5)	Raymond (2005)
	Effective visual control (T6)	Vinodh, Ramesh, and Arun (2016)
Standards and Regulations (S & R)	Environmental conservation (SR1)	Govindan, Diabat, and Shankar (2015); Bey, Hauschild, and McAloone (2013); Shankar, Kumar, and Kannan (2016)
	Emissions and global climate (SR2)	Moktadir et al. (2018); Siemieniuch, Sinclair, and Henshaw (2015)
	Safety and security (SR3)	Moktadir et al. (2018); Siemieniuch, Sinclair, and Henshaw (2015)
	Operational safety (SR4)	Wang et al. (2015);
	Compliance with regulations (SR5)	Bey, Hauschild, and McAloone (2013); Shankar, Kumar, and Kannan (2016);
Design (D)	Light weight parts (D1)	Khorram Niaki and Nonino (2017)
	Eco design (D2)	Govindan, Diabat, and Shankar (2015); Laverne et al. (2019)
	Flexibility in producing geometry (D3)	Mani, Lyons, and Gupta (2014)
	Ease of producing complex structure (D4)	Mani, Lyons, and Gupta (2014)
Process (P)	Cost saving (P1)	Niaki, Torabi, and Nonino (2019);
	Time saving (P2)	Niaki, Torabi, and Nonino (2019)
	On demand manufacturing (P3)	Attaran (2017)
	Enables mass customisation (P4)	Attaran (2017)
	No specialised tooling required (P5)	Mani, Lyons, and Gupta (2014)
	Quality (P6)	Bey, Hauschild, and McAloone (2013); Shankar, Kumar, and Kannan (2016)

Table 4. Best and worst driver specified by expert 1–4 for material category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Optimum resources utilisation	1,4	2
Reusing and recycling materials and packaging	2	3
Less material wastage	3	1,4

Table 5. Comparison of Best driver with other drivers (BO) by expert 1–4 for material category

Expert	Best to Others	Optimum resources utilisation	Reusing and recycling materials and packaging	Less material wastage
E1	Optimum resources utilisation	1	3	7
E2	Reusing and recycling materials and packaging	7	1	3
E3	Less material wastage	5	7	1
E4	Optimum resources utilisation	1	4	9

Table 6. Comparison of other driver with worst drivers (OW) by expert 1–4 for material category

Expert	E1	E2	E3	E4
Others to Worst	Less material wastage	Optimum resources utilisation	Reusing and recycling materials and packaging	Less material wastage
Optimum resources utilisation	7	1	3	9
Reusing and recycling materials and packaging	5	7	1	5
Less material wastage	1	5	7	1 R

Table 7. Weights of driver along with consistency for material category

Expert	Optimum resources utilisation	Reusing and recycling materials and packaging	Less material wastage	ξ^L
E1	0.6615	0.2615	0.0769	0.1231
E2	0.0769	0.6615	0.2615	0.1231
E3	0.1688	0.0909	0.7403	0.1039
E4	0.7222	0.2111	0.0667	0.1222
Final Weight	0.4074	0.3063	0.2864	0.1181

Consistency Ratio (CR) = $\frac{\xi }{ConsistencyIndex\left(CI\right)}$

CR = $\frac{0.1181}{1}$ and CI (n =3) = 1

CR = 0.1181

Table 8(b). Weights of drivers along with consistency for material category

Expert	Optimum resources utilisation	Reusing and recycling materials and packaging	Less material wastage	ξ^L
E1	0.6615	0.2615	0.0769	0.1231
E2	0.0769	0.6615	0.2615	0.1231
E3	0.1688	0.0909	0.7403	0.1039
E4	0.7222	0.2111	0.0667	0.1222
Final weight	0.4074	0.3063	0.2864	0.1181
Rank	1	2	3

CI (n =3) = 1,

CR = 0.1181/1

CR = 0.1181

Table 8(c). Weights of drivers along with consistency for management and stake holders category

Expert	Proper training and education	Incentives	Stake holder participation	Management support	Employee commitment towards sustainability	ξ^L
E1	0.5084	0.0446	0.0879	0.1539	0.2052	0.1070
E2	0.1539	0.0879	0.0446	0.2052	0.5084	0.1070
E3	0.0424	0.0836	0.4836	0.1952	0.1952	0.1018
E4	0.1952	0.0424	0.0836	0.4836	0.1952	0.1018
Final weight	0.2250	0.0646	0.1749	0.2595	0.2760	0.1044
Rank	3	5	4	2	1

CI (n =5) = 2.3,

CR = 0.1044/2.3

CR = 0.045

Table 8(d). Weights of drivers along with consistency for customer/ supplier/ competitor category

Expert	Customers’ expectations	Supplier commitment	Company image	Public pressure	Supply chain pressure	Competitor pressure towards greening	ξ^L
E1	0.4406	0.1334	0.0762	0.0387	0.1334	0.1778	0.0928
E2	0.1702	0.0370	0.4219	0.0730	0.1277	0.1702	0.0888
E3	0.1702	0.1277	0.1702	0.0730	0.0370	0.4219	0.0888
E4	0.1494	0.1494	0.1494	0.3701	0.0325	0.1494	0.0779
Final weight	0.2326	0.1119	0.2044	0.1387	0.0827	0.2298	0.0871
Rank	1	5	3	4	6	2

CI (n =6) = 3,

CR = 0.0871/3

CR = 0.029

Table 8(e). Weights of drivers along with consistency for collaboration and trends category

Expert	Market trends	Economic benefit	Collaboration between organisations	Long term survival in market	Collaborative decision making	ξ^L
E1	0.1377	0.1836	0.4551	0.1836	0.0399	0.0958
E2	0.0418	0.4770	0.1444	0.1444	0.1925	0.1004
E3	0.0399	0.1836	0.1836	0.1377	0.4551	0.0958
E4	0.1836	0.4551	0.1836	0.0399	0.1377	0.0958
Final weight	0.1008	0.3248	0.2417	0.1264	0.2063	0.0970
Rank	5	1	2	4	3

CI (n =5) = 2.3,

CR = 0.0970/2.3

CR = 0.042

Table 8(f). Weights of drivers along with consistency for technology category

Expert	Green innovation	Energy conservation	Technology competence	Technology adaptability	Time to develop new product	Effective visual control	ξ^L
E1	0.4219	0.1702	0.1277	0.1702	0.0730	0.0370	0.0888
E2	0.1702	0.1702	0.4219	0.1277	0.0370	0.0730	0.0888
E3	0.1702	0.4219	0.1702	0.1277	0.0730	0.0370	0.0888
E4	0.4673	0.1886	0.0808	0.0410	0.1414	0.0808	0.0984
Final weight	0.3074	0.2377	0.2002	0.1167	0.0811	0.0570	0.0912
Rank	1	2	3	4	5	6

CI (n =6) = 3,

CR = 0.0912/3

CR = 0.0304

Table 8(g). Weights of drivers along with consistency for standards and regulations category

Expert	Environmental conservation	Emissions & global climate	Safety & security	Operational safety	Compliance with regulations	ξ^L
E1	0.5084	0.2052	0.0446	0.0879	0.1539	0.1070
E2	0.1952	0.1952	0.0424	0.0836	0.4836	0.1018
E3	0.1844	0.4664	0.1106	0.0542	0.1844	0.0868
E4	0.5084	0.1539	0.0879	0.0446	0.2052	0.1070
Final weight	0.3491	0.2552	0.0714	0.0676	0.2568	0.1007
Rank	1	3	4	5	2

CI (n =5) = 2.3,

CR = 0.1007/2.3

CR = 0.0437

Table 8(h). Weights of drivers along with consistency for design category

Expert	Light weight parts	Eco design	Flexibility in producing geometry	Ease of producing complex structure	ξ^L
E1	0.2425	0.6009	0.1039	0.0527	0.1265
E2	0.6009	0.2425	0.0527	0.1039	0.1265
E3	0.0527	0.2425	0.6009	0.1039	0.1265
E4	0.2425	0.6009	0.0527	0.1039	0.1265
Final weight	0.2847	0.4217	0.2026	0.0911	0.1265
Rank	2	1	3	4

CI (n =4) = 1.63

CR = 0.1265/1.63

CR = 0.0776

Table 8(i). Weights of drivers along with consistency for process category

Expert	Cost saving	Time saving	On demand manufacturing	Enables mass customisation	No specialised tooling required	Quality	ξ^L
E1	0.1211	0.1614	0.1614	0.4000	0.1211	0.0351	0.0842
E2	0.1261	0.1261	0.4168	0.1261	0.1682	0.0366	0.0878
E3	0.0370	0.1277	0.1702	0.1702	0.4219	0.0730	0.0888
E4	0.0370	0.4219	0.1702	0.1702	0.1277	0.0730	0.0888
Final weight	0.0803	0.2093	0.2297	0.2166	0.2097	0.0544	0.0874
Rank	5	4	1	2	3	6

CI (n =6) = 3,

CR = 0.0874/3

CR = 0.0291

Table 8(a). Weights of Categories along with consistency

Expert	Material	Management and stake holders	Customer/ supplier/ competitor	Collaboration and trends	Technology	Standards and regulations	Design	process	ξ^L
E1	0.1369	0.0298	0.0587	0.1027	0.1369	0.0587	0.3394	0.1369	0.07144
E2	0.1312	0.0562	0.0984	0.0285	0.3251	0.0984	0.1312	0.1312	0.06843
E3	0.1312	0.0562	0.0285	0.0984	0.3251	0.0984	0.1312	0.1312	0.06843
E4	0.1369	0.0587	0.0587	0.1027	0.1369	0.0298	0.1369	0.3394	0.07144
Final weight	0.1331	0.0502	0.0611	0.0831	0.2310	0.0713	0.1847	0.1847	0.0699

CI (n =8) = 4.47,

CR = 0.0699/4.47

CR = 0.015

Table 9. Prioritised ranking of drivers of Sustainable Additive Manufacturing

Category	Category weight	Driver code	Weight	Global weight	Rank
Material (M)	0.1331	M1	0.4074	0.0542	4
		M2	0.3063	0.0408	8
		M3	0.2864	0.0381	12
Management and Stake Holders (M & SH)	0.0502	MSH1	0.225	0.0113	30
		MSH2	0.0646	0.0032	40
		MSH3	0.1749	0.0088	33
		MSH4	0.2595	0.0130	28
		MSH5	0.276	0.0139	26
Customer/ Supplier/ Competitor (CSC)	0.0611	CSC1	0.2326	0.0142	24
		CSC2	0.1119	0.0068	36
		CSC3	0.2044	0.0125	29
		CSC4	0.1387	0.0085	34
		CSC5	0.0827	0.0050	38
		CSC6	0.2298	0.0140	25
Collaboration and Trends (C & T)	0.0831	CT1	0.1008	0.0084	35
		CT2	0.3248	0.0270	14
		CT3	0.2417	0.0201	17
		CT4	0.1264	0.0105	31
		CT5	0.2063	0.0171	21
Technology (T)	0.2310	T1	0.3074	0.0710	2
		T2	0.2377	0.0549	3
		T3	0.2002	0.0462	6
		T4	0.1167	0.0269	15
		T5	0.0811	0.0187	18
		T6	0.057	0.0132	27
Standards and Regulations (S & R)	0.0713	SR1	0.3491	0.0249	16
		SR2	0.2552	0.0182	20
		SR3	0.0714	0.0051	37
		SR4	0.0676	0.0048	39
		SR5	0.2568	0.0183	19
Design (D)	0.1847	D1	0.2847	0.0526	5
		D2	0.4217	0.0779	1
		D3	0.2026	0.0374	13
		D4	0.0911	0.0168	22
Process (P)	0.1847	P1	0.0803	0.0148	23
		P2	0.2093	0.0386	11
		P3	0.2297	0.0424	7
		P4	0.2166	0.0400	9
		P5	0.2097	0.0387	10
		P6	0.0544	0.0100	32

Table 10. Benchmarking key results with previous studies

Research study	Technique used	Prioritised drivers/barriers
Mittal and Sangwan (2014)	Fuzzy TOPSIS	Future legislation, incentives and public pressure were the top three drivers of SM.
Ghazilla et al. (2015)	Delphi’s approach.	‘Increase in competition’ was the top priority driver. ‘Weak organization structures’ and ‘Inappropriate R&D facilities’ were top barriers of green manufacturing
Govindan, Diabat, and Shankar (2015)	Fuzzy-based MCDM approach	The top identified driver of green manufacturing was ‘Compliance with regulations’.
Agrawal and Vinodh (2019)	TISM	‘Flexibility in manufacturing’ was the most prominent factor affecting the sustainability of AM system.
Niaki, Torabi, and Nonino (2019)	Multi-stage survey	‘Customization’ and ‘Fabrication of complex design’ were the two top priority drivers for implementation of AM.

Figure 2. Drivers ranking by varying weights of criteria

Table A1 (a). Best and worst category specified by expert 1–4

Category	Identified as best by expert no.	Identified as worst by expert no.
Material	3
Management and stake holders		1
Customer/ Supplier/ Competitor		3
Collaboration and trends		2
Technology	2
Standards and regulations		4
Design	1
process	4

Table A1 (b). Comparison of best category with other categories (BO) by expert 1–4

Expert	Best to others	Material	Management and stake holders	Customer/ Supplier/ Competitor	Collaboration and trends	Technology	Standards and regulations	Design	process
E1	Design	3	9	7	4	3	7	1	3
E2	Technology	3	7	4	9	1	4	3	3
E3	Material	3	7	9	4	1	4	3	3
E4	process	3	7	7	4	3	9	3	1

Table A1 (c). Comparison of other categories with worst category (OW) by expert 1–4

Expert	E1	E2	E3	E4
Others to worst	Management and stake holders	Collaboration and trends	Customer/ Supplier/ Competitor	Standards and regulations
Material	7	7	7	7
Management and stake holders	1	3	3	3
Customer/ Supplier/ Competitor	3	5	1	3
Collaboration and trends	5	1	5	5
Technology	7	9	9	7
Standards and regulations	3	5	5	1
Design	9	7	7	7
process	7	7	7	9

Table A2 (a). Best and worst driver specified by expert 1–4 for material category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Optimum resources utilisation	1,4	2
Reusing and recycling materials and packaging	2	3
Less material wastage	3	1,4

Table A2 (b). Comparison of best driver with other drivers (BO) by expert 1–4 for material category

Expert	Best to others	Optimum resources utilisation	Reusing and recycling materials and packaging	Less material wastage
E1	Optimum resources utilisation	1	3	7
E2	Reusing and recycling materials and packaging	7	1	3
E3	Less material wastage	5	7	1
E4	Optimum resources utilisation	1	4	9

Table A2 (c). Comparison of other drivers with worst driver (OW) by expert 1–4 for material category

Expert	E1	E2	E3	E4
Others to worst	Less material wastage	Optimum resources utilisation	Reusing and recycling materials and packaging	Less material wastage
Optimum resources utilisation	7	1	3	9
Reusing and recycling materials and packaging	5	7	1	5
Less material wastage	1	5	7	1

Table A3 (a). Best and worst driver specified by expert 1–4 for Management and stake holders category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Proper training and education	1	3
Incentives		1,4
Stake holder participation	3	2
Management support	4
Employee commitment towards sustainability	2

Table A3 (b). Comparison of best driver with other drivers (BO) by expert 1–4 for management and stake holders category

Expert	Best to Others	Proper training and education	Incentives	Stake holder participation	Management support	Employee commitment towards sustainability
E1	Proper training and education	1	9	7	4	3
E2	Employee commitment towards sustainability	4	7	9	3	1
E3	Stake holder participation	9	7	1	3	3
E4	Management support	3	9	7	1	3

Table A3 (c). Comparison of other drivers with worst driver (OW) by expert 1–4 for management and stake holders category

Expert	E1	E2	E3	E4
Others to Worst	Incentives	Stake holder participation	Proper training and education	Incentives
Proper training and education	9	5	1	7
Incentives	1	3	3	1
Stake holder participation	3	1	9	3
Management support	5	7	7	9
Employee commitment towards sustainability	7	9	7	7

Table A4 (a). Best and worst driver specified by expert 1–4 for customer/ supplier/ competitor category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Customers’ expectations	1
Supplier commitment		2
Company image	2
Public pressure	4	1
Supply chain pressure		3,4
Competitor pressure towards greening	3

Table A4 (b). Comparison of best driver with other drivers (BO) by expert 1–4 for customer/ supplier/ competitor category

Expert	Best to others	Customers’ expectations	Supplier commitment	Company image	Public pressure	Supply chain pressure	Competitor pressure towards greening
E1	Customers’ expectations	1	4	7	9	4	3
E2	Company image	3	9	1	7	4	3
E3	Competitor pressure towards greening	3	4	3	7	9	1
E4	Public pressure	3	3	3	1	9	3

Table A4 (c). Comparison of other drivers with worst driver (OW) by expert 1–4 for customer/ supplier/ competitor category

Expert	E1	E2	E3	E4
Others to worst	Public pressure	Supplier commitment	Supply chain pressure	Supply chain pressure
Customers’ expectations	9	7	7	7
Supplier commitment	5	1	5	7
Company image	3	9	7	7
Public pressure	1	3	3	9
Supply chain pressure	5	5	1	1
Competitor pressure towards greening	7	7	9	7

Table A5 (a). Best and worst driver specified by expert 1–4 for collaboration and trends category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Market trends		2,3
Economic benefit	2,4
Collaboration between organisations	1
Long term survival in market		4
Collaborative decision making	3	1

Table A5 (b). Comparison of best driver with other drivers (BO) by expert 1–4 for collaboration and trends category

Expert	Best to others	Market trends	Economic benefit	Collaboration between organisations	Long term survival in market	Collaborative decision making
E1	Collaboration between organisations	4	3	1	3	9
E2	Economic benefit	9	1	4	4	3
E3	Collaborative decision making	9	3	3	4	1
E4	Economic benefit	3	1	3	9	4

Table A5 (c). Comparison of other drivers with worst driver (OW) by expert 1–4 for collaboration and trends category

Expert	E1	E2	E3	E4
Others to worst	Collaborative decision making	Market trends	Market trends	Long-term survival in market
Market trends	5	1	1	7
Economic benefit	7	9	7	9
Collaboration between organisations	9	5	7	7
Long term survival in market	7	5	5	1
Collaborative decision making	1	7	9	5

Table A6 (a). Best and worst driver specified by expert 1–4 for technology category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Green innovation	1,4
Energy conservation	3
Technology competence	2
Technology adaptability		4
Time to develop new product		2
Effective visual control		1,3

Table A6 (b). Comparison of best driver with other drivers (BO) by expert 1–4 for technology category

Expert	Best to others	Green innovation	Energy conservation	Technology competence	Technology adaptability	Time to develop new product	Effective visual control
E1	Green innovation	1	3	4	3	7	9
E2	Technology competence	3	3	1	4	9	7
E3	Energy conservation	3	1	3	4	7	9
E4	Green innovation	1	3	7	9	4	7

Table A6 (c). Comparison of other drivers with worst driver (OW) by expert 1–4 for technology category

Expert	E1	E2	E3	E4
Others to worst	Effective visual control	Time to develop new product	Effective visual control	Technology adaptability
Green innovation	9	7	7	9
Energy conservation	7	7	9	7
Technology competence	5	9	7	3
Technology adaptability	7	5	5	1
Time to develop new product	3	1	3	5
Effective visual control	1	3	1	3

Table A7 (a). Best and worst driver specified by expert 1–4 for standards and regulations category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Environmental conservation	1,4
Emissions & global climate	3
Safety & security		1,2
Operational safety		3,4
Compliance with regulations	2

Table A7 (b). Comparison of best driver with other drivers (BO) by expert 1–4 for standards and regulations category

Expert	Best to others	Environmental conservation	Emissions & global climate	Safety & security	Operational safety	Compliance with regulations
E1	Environmental conservation	1	3	9	7	4
E2	Compliance with regulations	3	3	9	7	1
E3	Emissions & global climate	3	1	5	7	3
E4	Environmental conservation	1	4	7	9	3

Table A7 (c). Comparison of other drivers with worst driver (OW) by expert 1–4 for standards and regulations category

Expert	E1	E2	E3	E4
Others to worst	Safety & security	Safety & security	Operational safety	Operational safety
Environmental conservation	9	7	5	9
Emissions & global climate	7	7	7	5
Safety & security	1	1	3	3
Operational safety	3	3	1	1
Compliance with regulations	5	9	5	7

Table A8 (a). Best and worst driver specified by expert 1–4 for design category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Light weight parts	2	3
Eco design	1,4
Flexibility in producing geometry	3	2,4
Ease of producing complex structure		1

Table A8 (b). Comparison of best driver with other drivers (BO) by expert 1–4 for design category

Expert	Best to others	Light weight parts	Eco design	Flexibility in producing geometry	Ease of of producing complex structure
E1	Eco design	3	1	7	9
E2	Light weight parts	1	3	9	7
E3	Flexibility in producing geometry	9	3	1	7
E4	Eco design	3	1	9	7

Table A8 (c). Comparison of other drivers with worst driver (OW) by expert 1–4 for design category

Expert	E1	E2	E3	E4
Others to worst	Ease of producing complex structure	Flexibility in producing geometry	Light weight parts	Flexibility in producing geometry
Light weight parts	7	9	1	7
Eco design	9	7	7	9
Flexibility in producing geometry	3	1	9	1
Ease of producing complex structure	1	3	3	3

Table A9 (a). Best and worst driver specified by expert 1–4 for process category

Driver	Identified as best by expert no.	Identified as worst by expert no.
Cost saving		3,4
Time saving	4
On demand manufacturing	2
Enables mass customisation	1
No specialised tooling required	3
Quality		1,2

Table A9 (b). Comparison of bbest driver with other drivers (BO) by expert 1–4 for process category

Expert	Best to others	Cost saving	Time saving	On demand manufacturing	Enables mass customisation	No specialised tooling required	Quality
E1	Enables mass customisation	4	3	3	1	4	9
E2	On demand manufacturing	4	4	1	4	3	9
E3	No specialised tooling required	9	4	3	3	1	7
E4	Time saving	9	1	3	3	4	7

Table A9 (c). Comparison of other drivers with worst driver (OW) by expert 1–4 for process category

Expert	E1	E2	E3	E4
Others to worst	Quality	Quality	Cost saving	Cost saving
Cost saving	5	5	1	1
Time saving	7	5	5	9
On demand manufacturing	7	9	7	7
Enables mass customisation	9	5	7	7
No specialised tooling required	5	7	9	5
Quality	1	1	3	3

Table A10. Weights of driver criteria for sensitivity analysis

Driver criteria	Normalised weight	Modified weights of driver criteria when design criteria varies from 0.1 to 0.9
		Run 1	Run 2	Run 3	Run 4	Run 4	Run 5	Run 6	Run 7	Run 8
Design (D)	0.1847	0.1	0.2	0.3	0.4	0.5	0.6	0.7	0.8	0.9
Process (P)	0.1847	0.213	0.19	0.166	0.142	0.119	0.095	0.071	0.047	0.024
Material (M)	0.1331	0.154	0.137	0.12	0.103	0.085	0.068	0.051	0.034	0.017
Management and Stake Holders (MSH)	0.0502	0.058	0.052	0.045	0.039	0.032	0.026	0.019	0.013	0.006
Customer/ Supplier/ Competitor (CSC)	0.0611	0.071	0.063	0.055	0.047	0.039	0.031	0.024	0.016	0.008
Collaboration and Trends (CT)	0.0831	0.096	0.085	0.075	0.064	0.053	0.043	0.032	0.021	0.011
Technology (T)	0.231	0.131	0.116	0.102	0.087	0.073	0.058	0.044	0.029	0.015
Standards and Regulations (SR)	0.0713	0.178	0.158	0.138	0.118	0.099	0.079	0.059	0.039	0.02

Table A11. Ranking of drivers for sensitivity analysis for different weights

Driver Code	Normalised ranking	Run 1	Run 2	Run 3	Run 4	Run 4	Run 5	Run 6	Run 7	Run 8	Run 9
M1	4	1	3	4	4	5	5	5	5	5	1
M2	8	4	6	7	8	8	8	8	8	8	4
M3	12	10	13	13	14	14	14	14	14	14	10
MSH1	30	27	28	28	28	28	28	28	28	28	27
MSH2	40	40	40	40	40	40	40	40	40	40	40
MSH3	33	33	34	34	34	34	34	34	34	34	33
MSH4	28	25	26	26	26	26	26	26	26	26	25
MSH5	26	23	24	24	24	24	24	24	24	24	23
CSC1	24	21	22	22	22	22	22	22	22	22	21
CSC2	36	37	37	37	37	37	37	37	37	37	37
CSC3	29	26	27	27	27	27	27	27	27	27	26
CSC4	34	34	35	35	35	35	35	35	35	35	34
CSC5	38	39	39	39	39	39	39	39	39	39	39
CSC6	25	22	23	23	23	23	23	23	23	23	22
CT1	35	35	36	36	36	36	36	36	36	36	35
CT2	14	13	15	16	16	16	16	16	16	16	13
CT3	17	17	18	19	19	19	19	19	19	19	17
CT4	31	29	30	30	30	30	30	30	30	30	29
CT5	21	19	20	20	20	20	20	20	20	20	19
T1	2	12	14	14	15	15	15	15	15	15	12
T2	3	14	16	17	17	17	17	17	17	17	14
T3	6	16	17	18	18	18	18	18	18	18	16
T4	15	24	25	25	25	25	25	25	25	25	24
T5	18	32	33	33	33	33	33	33	33	33	32
T6	27	38	38	38	38	38	38	38	38	38	38
SR1	16	2	4	5	5	6	6	6	6	6	2
SR2	20	7	10	10	11	11	11	11	11	11	7
SR3	37	28	29	29	29	29	29	29	29	29	28
SR4	39	30	31	31	31	31	31	31	31	31	30
SR5	19	6	8	9	10	10	10	10	10	10	6
D1	5	15	2	2	2	2	2	2	2	2	15
D2	1	11	1	1	1	1	1	1	1	1	11
D3	13	18	9	3	3	3	3	3	3	3	18
D4	22	36	19	15	6	4	4	4	4	4	36
P1	23	20	21	21	21	21	21	21	21	21	20
P2	11	9	12	12	13	13	13	13	13	13	9
P3	7	3	5	6	7	7	7	7	7	7	3
P4	9	5	7	8	9	9	9	9	9	9	5
P5	10	8	11	11	12	12	12	12	12	12	8
P6	32	31	32	32	32	32	32	32	32	32	31

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