Analyzing the Barriers to Industry 4.0 Through Best-Worst Method

doi:10.23940/ijpe.20.01.p4.2736

Abstract

Abstract:

Presently, mankind is in the era of rapid advancement and technological change. The product lifecycle has been shortening dramatically and the manufacturing industry is moving from mass customization of products to high personalization of mass products. This era is widely known as fourth Industrial revolution or Industry 4.0. It seems that sooner or later every society has to adopt and implement it. In this paper, an attempt has been made to identify, categorize, and prioritize the barriers in-front of present manufacturing industry in implementation of widely acclaimed Industry 4.0 practices. The ranking of the challenges/ barriers in adoption of this highly sophisticated manufacturing are identified and ranked categorically as well as across the categories with the help of a survey based empirical study. Such obtained ranking of barriers are optimized through Best-Worst Method. The results provide the insights of barriers, their prominence and priorities of our industries, mainly Indian, in adoption of this era of digital, intelligent and connected manufacturing.

Key words: Industry 4.0, barriers to Industry 4.0, challenges to Industry 4.0, prominence ranking, Best Worst Method

Shailendra Kumar, Mohd Suhaib, and Mohammad Asjad. Analyzing the Barriers to Industry 4.0 Through Best-Worst Method [J]. Int J Performability Eng, 2020, 16(1): 27-36.

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Figures/Tables 7

Table 1

Major potential barriers/impediments in implementation of Industry 4.0"

Category	S. No./ Code	Name of impediment/Barrier	Brief description
Technological	B-1	Lack of IT Infrastructure [2, 15]	Bandwidth, speed, protocols, computing facilities, etc
	B-2	Lack of huge data analytic matured techniques [14]	Able to handle and to analyze the huge volume of manufacturing specific data along with other technological and business data
	B-3	Missing standards [2, 12, 15]	Lack of standards/ unclear standards/ reference architecture/ dynamic implementation plan
	B-4	Data insecurity [2, 11, 14-15]	Risk of data loss, manipulation, and privacy
	B-5	Intelligent decision making system and negotiation mechanism [14]	Artificial intelligent based self learning/ adaptable system backed with the knowledge of experience, expertise, and data available. It is required to infuse autonomous intelligent decision making in the system.
	B-6	Modular and flexible smart devices which can adapt itself to any change [14]	Devices could be grouped, regrouped, and worked together with integration to IT technologies in such a distributed, flexible, and smart system.
	B-7	Low maturity level and integration of required technologies [2, 11]	Lack of Matured Technologies required to integrate the physical hardware, software and data analytics
	B-8	Very high complexity [2, 11]	Highly complex in terms of both physical and technological
	B-9	Poor compatibility of current solutions/ devices with existing systems [15]	Presently available devices/ Machines/ artifacts and technologies are not fully compatible with the required
Economical	B-10	High investment [11, 14-15]	It needs a very huge capital investment, lack of transparent cost-benefit analyzes, lack of clear comprehension about benefits
Economical	B-11	Missing cooperation partners and funding [2]	Similar to financial institutions
Socio-Economical	B-12	Lack of management support [2, 15]	Organizational and process change/ difficulty to form an Industry 4.0 strategy
Socio-Economical	B-13	Missing government support [2]	E.g. funding, regulations, education, training
Social	B-14	Unwanted strain to the man power [2, 15]	Employment disruption, possible job loss
	B-15	Lack of properly qualified/ skilled man power [15]	Lack of knowledge of required technical know-how and skills to the existing and available man power
	B-16	Lack of regulatory mechanism [9]	Lack of clear laws and legal support, etc

Table 1

∑ j W j = 1

(1)

|W_B - a_BjW_j| ≤

ξ L

for all j
|W_j - a_jW W_W| ≤

ξ L

for all j

(2)

Table 2

Summary of survey response ratings"

Category	Name or Code	Question/ Barrier	No. of Responses	Max, Min Value	Mean of all Response ratings	Standard Deviation (sample) σ	Mode	Frequency of Mode Value	Median	Mean of values under (mean of all +/- 2σ) = M	Rank (in category)	Rank (Overall)
Category	Name or Code	Question/ Barrier	No. of Responses	Max, Min Value	Mean of all Response ratings	Standard Deviation (sample) σ	Mode	Frequency of Mode Value	Median	Mean of values under (mean of all +/- 2σ) = M	Based on M
Technological	B-1	Lack of IT Infrastructure: bandwidth, speed, protocols, computing facilities, etc	36	10, 0	6.1	3.1	9	6	7	9.07	1	1
	B-2	Lack of matured data analytic techniques able to handle and to analyse the huge volume of manufacturing specific data along with other technological and business data	28	10, 1	6.1	2.7	8	7	6	6.40	9	14
	B-3	Missing standards: Lack of standards/ unclear standards/ reference architecture/ dynamic implementation plan	37	10, 2	7.5	2.3	9	8	8	7.70	2	4
	B-4	Data insecurity: Risk of data loss, manipulation, and privacy	37	10, 0	6.6	2.8	9	6	7	7.22	4	8
	B-5	Intelligent decision making system and negotiation mechanism: An artificial intelligent based self learning/ adaptable system backed with the knowledge of experience, expertise, and data available. It is required to infuse autonomous intelligent decision making in the system	36	10, 0	6.5	2.9	9	8	7	6.95	6	11
	B-6	Modular and flexible smart devices which can adapt itself to any change such that could be grouped, regrouped, and worked together with integration to IT technologies in such a distributed, flexible, and smart system.	36	10, 0	6.3	3.0	9	8	7	6.41	8	13
	B-7	Low maturity level and integration of required technologies: Lack of Matured Technologies required to integrate the physical manufacturing hardware, software and data analytics	36	10, 1	6.6	2.3	9	7	7	6.66	7	12
	B-8	Very high complexity: In terms of both physical and technological	37	10, 1	6.7	2.5	9	11	7	7.03	5	10
	B-9	Poor compatibility of current solutions/ devices with existing systems: Presently available devices/ Machines/ artifacts and technologies are not fully compatible with the required	36	10, 1	7.2	2.4	9	11	8	7.46	3	5
Economical	B-10	Needs huge investment: Lack of transparent cost-benefit analyzes, lack of clear comprehension about benefits are there.	37	10, 2	7.7	2.0	9	12	8	8.05	1	3
Economical	B-11	Missing cooperation partners and funding like financial institutions	37	10, 0	7.1	2.5	9	9	8	7.36	2	7
Socio-Economical	B-12	Lack of management support: organizational and process change/ difficulty to form an Industry 4.0 strategy	35	10, 1	7.5	2.3	9	9	8	8.08	1	2
Socio-Economical	B-13	Missing government support e.g. funding, regulations, education, training	35	10, 2	6.8	2.5	9	9	7	7.20	2	9
Social	B-14	Unwanted strain to the man power, employment disruption, possible job loss	36	10, 0	6.1	3.2	9	10	7	6.04	3	16
	B-15	Lack of properly qualified/ skilled man power: lack of knowledge of required technical know-how and skills to the existing and available man power	36	10, 0	7.2	2.3	8	9	8	7.45	1	6
	B-16	Lack of regulatory mechanism like clear laws and legal support, etc	35	10, 0	6.2	3.2	9	8	7	6.31	2	15

Table 2

Table 3

Figure 1.

Table 4

Barrier name/ Code	Mean rating value (M)	Rank according to (M)	Ratio Best to others, B	Calibrated value of (B) on 1 to 9 scale	Ratio others to worst, W	Calibrated value of (W) on 1 to 9 scale
B-1	9.07	1 (Best)	1	1	1.42	9
B-2	6.4	9 (Worst)	1.42	9	1.00	1
B-3	7.7	2	1.18	4	1.20	5
B-4	7.22	4	1.26	6	1.13	3
B-5	6.95	6	1.31	7	1.09	3
B-6	6.41	8	1.41	9	1.00	1
B-7	6.66	7	1.36	8	1.04	2
B-8	7.03	5	1.29	7	1.10	3
B-9	7.46	3	1.22	5	1.17	4