A systematic investigation of the barriers to effective implementation of human-robot assembly line: an integrated multi-criteria decision-making approach

Figures & data

Figure 1. Definition of factors influencing the implementation of HRAL.

Figure 2. Assembly line evaluation map based on automation and flexibility.

Figure 3. Framework for analysing HRAL component features and system features.

Figure 4. Skillsets of components on HRAL.

Table 1. Interrelationship between component features and system features of HRAL.

		Human skillset				Robotic skillset			Collaborative skillset
		Cognition	Intelligence	Agility	Stochasticity	Strength	Tirelessness	Repeatability	Lightweight	Safe Speed	Perception	Usability
		H1	H1	H2	H3	H4	R1	R2	R3	C1	C2	C3
Improving flexibility and reconfigurability	L1	▲	▲	▲					▲			▲
Improving ergonomics and safety	L2					▲	▲	▲	▲	▲	▲
Reduce cycle time and idle time	L3	▲	▲			▲	▲	▲
Limitation in accuracy and repeatability	L4				▲				▲			▲
Limitation in payload and productivity	L5				▲				▲	▲
Potential disorder and breakdown	L6			▲	▲		▲

Figure 5. Cognitive map showing the causal relationships between component features and system features of HRAL.

Figure 6. Diagram of the Triple-I framework and causes of barriers to HRAL implementation.

Table 2. Barriers of HRAL implementation based on the Triple-I framework.

Categories	Barriers		Reference
Intrinsic barriers	I-B1	Limitations in accuracy and repeatability	(Hu et al. 2022; Safeea, Bearee, and Neto 2017; Wang et al. 2018)
	I-B2	Limitations in payload and productivity	(Bänziger, Kunz, and Wegener 2020; International Organization for Standardization 2016; Mazzocchi et al. 2015)
	I-B3	Potential disorder and break down	(Casalino et al. 2019; Faccio et al. 2022; Kopp, Baumgartner, and Kinkel 2021; Stadnicka and Antonelli 2019; Zhang et al. 2022)
Integration barriers	II-B1	Lack of corresponding line feeding subsystem	(Aaltonen and Salmi 2019; Battini et al. 2009; Schmid and Limère 2019)
	II-B2	Lack of universal interaction interface	(Gustavsson et al. 2018; Kildal et al. 2018; Tsarouchi, Makris, and Chryssolouris 2016)
	II-B3	Lack of datasets to balance HRAL	(Boysen, Schulze, and Scholl 2021; Kousi et al. 2021; Li, Janardhanan, and Tang 2021)
	II-B4	Complexity in integrating with existing line	(Malik and Bilberg 2019; Sadrfaridpour, Saeidi, and Wang 2016)
Industrial barriers	III-B1	Lack of standardisation and metrics	(Grahn et al. 2018; Nimawat and Gidwani 2021)
	III-B2	Lack of knowledge and trust among workers	(Charalambous, Fletcher, and Webb 2015; Kumar, Savur, and Sahin 2021; Lewis and Boyer 2002)
	III-B3	High acquisition and maintenance costs	(Cohen, Shoval, and Faccio 2019; De Backer et al. 2018; Guerin et al. 2015; Knudsen and Kaivo-Oja 2020; Silva, Simões, and Blanc 2022)

Figure 7. Proposed integrated MCDM model for HRAL implementation.

Slightly updated figure.

Table 3. Details of experts.

Sector	Position of experts		Experience
Industry practitioner (Industry robot provider)	Expert 1	Automation Engineer	Engage in the design of HRC workstations
Industry practitioner (Automobile engine Manufacturer)	Expert 2	Assembly Line Integrator	Undertake the hardware and software integration of assembly system
	Expert 3	Manufacturing Process Engineer	Responsible for planning and implementing the assembly process
	Expert 4	Production Manager	Responsible for the production management of an automation industry
Academia (Production systems research)	Expert 5	University Academician	Focus on the research of RAL and HRAL balance problem
	Expert 6	University Academician	Focus on product management problem in manufacturing systems

Table 4. Alternatives of HRAL configuration.

Alternative of HRAL configuration	Types of collaborative strategy (ISO/TS 15,066:2016)	Description
Configuration 1 (C1)	Safety-rated monitored stop (SMS)	Collaborative robots designed for low human interaction, employing a traditional pause mechanism, while the cobots halt operations upon human entry and automatically resume after exit.
Configuration 2 (C2)	Speed and separation monitoring (SSM)	Collaborative robots equipped with sensors to monitor proximity to human workers, slowing down or stopping operation based on the distance between the robot and the worker.
Configuration 3 (C3)	Power and force limiting (PFL)	Collaborative robots with collision sensors to limit power and force when interacting with human workers, ensuring safety without the need for external safety devices or barriers.
Configuration 4 (C4)	Hand guiding (HG)	Collaborative robots that can be manually guided by a human worker’s hand for programming and retraining purposes.

Table 5. Linguistic terms and rating (Lo et al. 2019).

Rating	Linguistic terms
10	Very hazardous (VH)
9	Hazardous (H)
8	Extreme (E)
7	Major (MA)
6	Significant (S)
5	Moderate (MO)
4	Low (L)
3	Minor (MI)
2	Very minor (VM)
1	None (N)

Table 6. The weights of main categories.

Categories	Expert 1	Expert 2	Expert 3	Expert 4	Expert 5	Expert 6	Category weight
Intrinsic barriers	0.594 ^(B)	0.339	0.589 ^(B)	0.313	0.596 ^(B)	0.628 ^(B)	0.510
Integration barriers	0.344	0.589 ^(B)	0.339	0.125 ^(W)	0.327	0.140 ^(W)	0.311
Industrial barriers	0.063 ^(W)	0.071 ^(W)	0.071 ^(W)	0.563 ^(B)	0.077 ^(W)	0.233	0.180
ξ^L (consistency check)	0.094	0.089	0.089	0.063	0.058	0.070

Table 7. The local weights of barriers.

Barriers	Expert 1	Expert 2	Expert 3	Expert 4	Expert 5	Expert 6	Local weight
I-B1	0.339	0.105^(W)	0.316	0.661^(B)	0.308	0.762^(B)	0.415
I-B2	0.589^(B)	0.579 ^(B)	0.579^(B)	0.237	0.615^(B)	0.143	0.457
I-B3	0.071^(W)	0.316	0.105^(W)	0.102^(W)	0.077^(W)	0.095^(W)	0.128
ξ^L	0.089	0.053	0.053	0.051	0.077	0.095
II-B1	0.118	0.186	0.103^(W)	0.056^(W)	0.172	0.128	0.127
II-B2	0.074^(W)	0.051 ^(W)	0.259	0.103	0.259	0.213	0.160
II-B3	0.294	0.483^(B)	0.466^(B)	0.533^(B)	0.103^(W)	0.097^(W)	0.329
II-B4	0.515^(B)	0.280	0.172	0.308	0.466^(B)	0.562^(B)	0.384
ξ^L	0.074	0.076	0.052	0.084	0.052	0.078
III-B1	0.235	0.594^(B)	0.743^(B)	0.071^(W)	0.143	0.118^(W)	0.317
III-B2	0.118^(W)	0.063^(W)	0.099^(W)	0.589^(B)	0.095^(W)	0.235	0.200
III-B3	0.647^(B)	0.344	0.158	0.339	0.762^(B)	0.647^(B)	0.483
ξ^L	0.059	0.094	0.050	0.089	0.095	0.059

Table 8. Final ranking of the sub-barriers for implementing HRAL.

Rank	Barriers		Category	Global weight
1	I-B2	Limitations in payload and productivity	Intrinsic barriers	0.233
2	I-B1	Limitations in accuracy and repeatability	Intrinsic barriers	0.212
3	II-B4	Complexity in integrating with existing line	Integration barriers	0.119
4	II-B3	Lack of datasets to balance HRAL	Integration barriers	0.102
5	III-B3	High acquisition and maintenance costs	Industrial barriers	0.087
6	I-B3	Potential disorder and breakdown	Intrinsic barriers	0.065
7	III-B1	Lack of standardisation and metrics	Industrial barriers	0.057
8	II-B2	Lack of universal interaction interface	Integration barriers	0.050
9	II-B1	Lack of corresponding line feeding subsystem	Integration barriers	0.040
10	III-B2	Lack of knowledge and trust among workers	Industrial barriers	0.036

Table 9. Initial evaluation matrix for HRAL configuration alternatives.

Alternative	I-B1	I-B2	I-B3	II-B1	II-B2	II-B3	II-B4	III-B1	III-B2	III-B3
Configuration 1 (C1)	3.167	2.833	3.167	2.500	4.167	5.500	4.000	2.833	6.667	5.000
Configuration 2 (C2)	6.333	4.833	3.833	5.667	5.667	7.667	7.167	5.167	5.833	6.167
Configuration 3 (C3)	7.000	7.667	5.333	3.667	2.833	4.833	5.833	4.167	3.000	4.667
Configuration 4 (C4)	7.167	7.500	6.167	4.167	5.167	6.500	5.500	5.500	4.167	6.833

Table 10. Weighted normalised decision matrix.

	I-B1	I-B2	I-B3	II-B1	II-B2	II-B3	II-B4	III-B1	III-B2	III-B3
wi	0.212	0.233	0.065	0.040	0.050	0.102	0.119	0.057	0.036	0.087
C1	0.055^(+)	0.055^(+)	0.022^(+)	0.012^(+)	0.023	0.045	0.041^(+)	0.018^(+)	0.023^(–)	0.038
C2	0.109	0.093	0.026	0.027^(–)	0.031^(–)	0.063^(–)	0.074^(–)	0.032	0.021	0.047
C3	0.121	0.148^(–)	0.036	0.018	0.015^(+)	0.040^(+)	0.061	0.026	0.011^(+)	0.035^(+)
C4	0.124^(–)	0.144	0.042^(–)	0.020	0.028	0.053	0.057	0.035^(–)	0.015	0.052^(–)

Table 11. Separation distance and relative closeness of alternatives.

Alternative	Collaborative strategy	$d_i^{+}$	$d_i^{-}$	$C_i^{-}$	Rank
Configuration 1	Safety-rated monitored stop (SMS)	0.016	0.127	0.888	1
Configuration 2	Speed and separation monitoring (SSM)	0.084	0.059	0.413	2
Configuration 3	Power and force limiting (PFL)	0.117	0.040	0.255	3
Configuration 4	Hand guiding (HG)	0.120	0.023	0.161	4

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