Method for assessing the obsolescence of manufacturing equipment based on the triple bottom line

Schlickmann, Marcelo Niehues; Ferreira, João Carlos Espíndola; Pereira, Abner do Canto

doi:10.1590/0103-6513.20190003

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Research Article • Prod. 30 • 2020 • https://doi.org/10.1590/0103-6513.20190003 copy

Method for assessing the obsolescence of manufacturing equipment based on the triple bottom line

Authorship SCIMAGO INSTITUTIONS RANKINGS

Abstract

Paper aims

This paper proposes a method for the assessment of equipment obsolescence, which includes the economic, environmental and social dimensions that compose the triple bottom line.

Originality

This paper describes a novel method that allows a complete evaluation of the state of use of a machine, besides the traditional economic-functional analysis, as well as its application in a large electric machines manufacturing company.

Research method

Analytic Hierarchy Process (AHP) multicriteria analysis is used, allowing a comparative and flexible assessment of the equipment.

Main findings

Even if there is no economic justification for replacing the equipment considering the financial return on investment, the machine can be considered obsolete from a sustainable point of view, due to its inadequate environmental and social performance.

Implications for theory and practice

Applying sustainability concepts in the manufacturing environment, more precisely in the machines on the shop floor, is very important to ensure cleaner production.

Keywords:
Sustainable manufacturing; Equipment obsolescence; Triple Bottom Line (TBL); Analytic Hierarchy Process (AHP)

Dimension	Aspect	Joung et al. (2013)Joung, C. B., Carrell, J., Sarkar, P., & Feng, S. C. (2013). Categorization of indicators for sustainable manufacturing. Ecological Indicators, 24, 148-157. http://dx.doi.org/10.1016/j.ecolind.2012.05.030. http://dx.doi.org/10.1016/j.ecolind.2012...	Linke et al. (2013)Linke, B. S., Corman, G. J., Dornveld, D. A., & Tönissen, S. (2013). Sustainability indicators for discrete manufacturing processes applied to grinding technology. Journal of Manufacturing Systems, 32(4), 556-563. http://dx.doi.org/10.1016/j.jmsy.2013.05.005. http://dx.doi.org/10.1016/j.jmsy.2013.05...	Sari et al. (2015)Sari, E., Shaharoun, A. M., Ma’aram, A., & Yazid, A. M. (2015). Sustainable maintenance performance measures: a pilot survey in Malaysian automotive companies. Procedia CIRP, 26, 443-448. http://dx.doi.org/10.1016/j.procir.2014.07.163. http://dx.doi.org/10.1016/j.procir.2014....	Amrina & Vilsi (2015)Amrina, E., & Vilsi, A. L. (2015). Key performance indicators for sustainable manufacturing assessment in cement industry. Procedia CIRP, 26, 19-23. http://dx.doi.org/10.1016/j.procir.2014.07.173. http://dx.doi.org/10.1016/j.procir.2014....	Ocampo et al. (2015)Ocampo, L. A., Vergara, V. G., Impas, C., Tordillo, J. A., & Pastoril, J. (2015). Identifying critical indicators in sustainable manufacturing using analytic hierarchy process (AHP). Journal of Manufacturing and Industrial Engineering, 14(3-4), 1-8. http://dx.doi.org/10.12776/mie.v14i3-4.444. http://dx.doi.org/10.12776/mie.v14i3-4.4...	Zhang & Haapala (2015)Zhang, H., & Haapala, K. R. (2015). Integrating sustainable manufacturing assessment into decision making for a production work cell. Journal of Cleaner Production, 105, 52-63. http://dx.doi.org/10.1016/j.jclepro.2014.01.038. http://dx.doi.org/10.1016/j.jclepro.2014...	Singh et al. (2016)Singh, S., Olugu, E. U., & Musa, S. N. (2016). Development of sustainable manufacturing decision making models for small and medium enterprises. Procedia CIRP, 40, 608-613. http://dx.doi.org/10.1016/j.procir.2016.01.142. http://dx.doi.org/10.1016/j.procir.2016....	Helleno et al. (2017)Helleno, A. L., Moraes, A. J. I., & Simon, T. S. (2017). Integrating sustainability indicators and lean manufacturing to assess manufacturing processes: Application case studies in Brazilian industry. Journal of Cleaner Production, 153, 405-416. http://dx.doi.org/10.1016/j.jclepro.2016.12.072. http://dx.doi.org/10.1016/j.jclepro.2016...
Economic	Cost	x	x	x	x	x	x	x	x
	Productivity	x	x	x	x	x	x		x
	Quality	x		x				x	x
	Guarantees and duties	x						x	x
Environmental	Production inputs consumption	x	x	x	x	x	x	x	x
	Material usage	x	x	x	x	x	x	x	x
	Land use	x		x		x
	Emission, waste and effluents	x	x	x	x	x	x	x	x
Social	Labour intensity		x				x
	Occupational health	x		x	x	x	x	x	x
	Worker training and satisfaction	x		x	x	x		x	x
	Job safety	x		x	x	x	x	x

Economic Aspects	Sustainability Indicators
Cost	Cost of direct and indirect labor, cost of maintenance, cost of energy consumption, materials and supplies, cost of inventory, etc.
Productivity	Cycle time, production rate, overall equipment effectiveness (OEE), availability of equipment, quantity of material produced, etc.
Quality	Relation between non-conforming parts and good parts, capacity index and process performance (P_p and P_pk), etc.
Guarantees and duties	Cost of treatment of fluids, cost of treatment of waste, cost resulting from worker indemnities, etc.

Source: Joung et al. (2013)Joung, C. B., Carrell, J., Sarkar, P., & Feng, S. C. (2013). Categorization of indicators for sustainable manufacturing. Ecological Indicators, 24, 148-157. http://dx.doi.org/10.1016/j.ecolind.2012.05.030.
http://dx.doi.org/10.1016/j.ecolind.2012... , Linke et al. (2013)Linke, B. S., Corman, G. J., Dornveld, D. A., & Tönissen, S. (2013). Sustainability indicators for discrete manufacturing processes applied to grinding technology. Journal of Manufacturing Systems, 32(4), 556-563. http://dx.doi.org/10.1016/j.jmsy.2013.05.005.
http://dx.doi.org/10.1016/j.jmsy.2013.05... , Sari et al. (2015)Sari, E., Shaharoun, A. M., Ma’aram, A., & Yazid, A. M. (2015). Sustainable maintenance performance measures: a pilot survey in Malaysian automotive companies. Procedia CIRP, 26, 443-448. http://dx.doi.org/10.1016/j.procir.2014.07.163.
http://dx.doi.org/10.1016/j.procir.2014.... , Amrina & Vilsi (2015)Amrina, E., & Vilsi, A. L. (2015). Key performance indicators for sustainable manufacturing assessment in cement industry. Procedia CIRP, 26, 19-23. http://dx.doi.org/10.1016/j.procir.2014.07.173.
http://dx.doi.org/10.1016/j.procir.2014.... , Ocampo et al. (2015)Ocampo, L. A., Vergara, V. G., Impas, C., Tordillo, J. A., & Pastoril, J. (2015). Identifying critical indicators in sustainable manufacturing using analytic hierarchy process (AHP). Journal of Manufacturing and Industrial Engineering, 14(3-4), 1-8. http://dx.doi.org/10.12776/mie.v14i3-4.444.
http://dx.doi.org/10.12776/mie.v14i3-4.4... , Zhang & Haapala (2015)Zhang, H., & Haapala, K. R. (2015). Integrating sustainable manufacturing assessment into decision making for a production work cell. Journal of Cleaner Production, 105, 52-63. http://dx.doi.org/10.1016/j.jclepro.2014.01.038.
http://dx.doi.org/10.1016/j.jclepro.2014... , Singh et al. (2016)Singh, S., Olugu, E. U., & Musa, S. N. (2016). Development of sustainable manufacturing decision making models for small and medium enterprises. Procedia CIRP, 40, 608-613. http://dx.doi.org/10.1016/j.procir.2016.01.142.
http://dx.doi.org/10.1016/j.procir.2016.... , Helleno et al. (2017)Helleno, A. L., Moraes, A. J. I., & Simon, T. S. (2017). Integrating sustainability indicators and lean manufacturing to assess manufacturing processes: Application case studies in Brazilian industry. Journal of Cleaner Production, 153, 405-416. http://dx.doi.org/10.1016/j.jclepro.2016.12.072.
http://dx.doi.org/10.1016/j.jclepro.2016... .

Environmental Aspects	Sustainability Indicators
Consumption of inputs	Consumption of electric energy, gases, water, oils, etc.
Material usage	Raw material used, consumption of tools, filters, use of restricted materials, etc.
Occupied area	Total area required for installation of the machine and accessories, area required for the material being processed, etc.
Emissions, waste and effluents	Quantity of oil discarded, level of water loss, emission of CO₂ and other gases, emission of toxic substances, etc.

Source: Joung et al. (2013)Joung, C. B., Carrell, J., Sarkar, P., & Feng, S. C. (2013). Categorization of indicators for sustainable manufacturing. Ecological Indicators, 24, 148-157. http://dx.doi.org/10.1016/j.ecolind.2012.05.030.
http://dx.doi.org/10.1016/j.ecolind.2012... , Linke et al. (2013)Linke, B. S., Corman, G. J., Dornveld, D. A., & Tönissen, S. (2013). Sustainability indicators for discrete manufacturing processes applied to grinding technology. Journal of Manufacturing Systems, 32(4), 556-563. http://dx.doi.org/10.1016/j.jmsy.2013.05.005.
http://dx.doi.org/10.1016/j.jmsy.2013.05... , Sari et al. (2015)Sari, E., Shaharoun, A. M., Ma’aram, A., & Yazid, A. M. (2015). Sustainable maintenance performance measures: a pilot survey in Malaysian automotive companies. Procedia CIRP, 26, 443-448. http://dx.doi.org/10.1016/j.procir.2014.07.163.
http://dx.doi.org/10.1016/j.procir.2014.... , Amrina & Vilsi (2015)Amrina, E., & Vilsi, A. L. (2015). Key performance indicators for sustainable manufacturing assessment in cement industry. Procedia CIRP, 26, 19-23. http://dx.doi.org/10.1016/j.procir.2014.07.173.
http://dx.doi.org/10.1016/j.procir.2014.... , Ocampo et al. (2015)Ocampo, L. A., Vergara, V. G., Impas, C., Tordillo, J. A., & Pastoril, J. (2015). Identifying critical indicators in sustainable manufacturing using analytic hierarchy process (AHP). Journal of Manufacturing and Industrial Engineering, 14(3-4), 1-8. http://dx.doi.org/10.12776/mie.v14i3-4.444.
http://dx.doi.org/10.12776/mie.v14i3-4.4... , Zhang & Haapala (2015)Zhang, H., & Haapala, K. R. (2015). Integrating sustainable manufacturing assessment into decision making for a production work cell. Journal of Cleaner Production, 105, 52-63. http://dx.doi.org/10.1016/j.jclepro.2014.01.038.
http://dx.doi.org/10.1016/j.jclepro.2014... , Singh et al. (2016)Singh, S., Olugu, E. U., & Musa, S. N. (2016). Development of sustainable manufacturing decision making models for small and medium enterprises. Procedia CIRP, 40, 608-613. http://dx.doi.org/10.1016/j.procir.2016.01.142.
http://dx.doi.org/10.1016/j.procir.2016.... , Helleno et al. (2017)Helleno, A. L., Moraes, A. J. I., & Simon, T. S. (2017). Integrating sustainability indicators and lean manufacturing to assess manufacturing processes: Application case studies in Brazilian industry. Journal of Cleaner Production, 153, 405-416. http://dx.doi.org/10.1016/j.jclepro.2016.12.072.
http://dx.doi.org/10.1016/j.jclepro.2016... .

Social Aspects	Sustainability Indicators
Labor intensity	Energy consumed during machine operation, energy consumption in setup, etc.
Occupational health	Level of noise and vibration, degree of unhealthiness; problems of ergonomics, lighting and ventilation, etc.
Training and satisfaction	Degree of instruction required for the operator, hours of training, level of satisfaction to perform the task, career development, etc.
Job safety	Number of accidents at work, risk of electric, mechanical and chemical accidents, danger degree of the task, etc.

Source: Joung et al. (2013)Joung, C. B., Carrell, J., Sarkar, P., & Feng, S. C. (2013). Categorization of indicators for sustainable manufacturing. Ecological Indicators, 24, 148-157. http://dx.doi.org/10.1016/j.ecolind.2012.05.030.
http://dx.doi.org/10.1016/j.ecolind.2012... , Linke et al. (2013)Linke, B. S., Corman, G. J., Dornveld, D. A., & Tönissen, S. (2013). Sustainability indicators for discrete manufacturing processes applied to grinding technology. Journal of Manufacturing Systems, 32(4), 556-563. http://dx.doi.org/10.1016/j.jmsy.2013.05.005.
http://dx.doi.org/10.1016/j.jmsy.2013.05... , Sari et al. (2015)Sari, E., Shaharoun, A. M., Ma’aram, A., & Yazid, A. M. (2015). Sustainable maintenance performance measures: a pilot survey in Malaysian automotive companies. Procedia CIRP, 26, 443-448. http://dx.doi.org/10.1016/j.procir.2014.07.163.
http://dx.doi.org/10.1016/j.procir.2014.... , Amrina & Vilsi (2015)Amrina, E., & Vilsi, A. L. (2015). Key performance indicators for sustainable manufacturing assessment in cement industry. Procedia CIRP, 26, 19-23. http://dx.doi.org/10.1016/j.procir.2014.07.173.
http://dx.doi.org/10.1016/j.procir.2014.... , Ocampo et al. (2015)Ocampo, L. A., Vergara, V. G., Impas, C., Tordillo, J. A., & Pastoril, J. (2015). Identifying critical indicators in sustainable manufacturing using analytic hierarchy process (AHP). Journal of Manufacturing and Industrial Engineering, 14(3-4), 1-8. http://dx.doi.org/10.12776/mie.v14i3-4.444.
http://dx.doi.org/10.12776/mie.v14i3-4.4... , Zhang & Haapala (2015)Zhang, H., & Haapala, K. R. (2015). Integrating sustainable manufacturing assessment into decision making for a production work cell. Journal of Cleaner Production, 105, 52-63. http://dx.doi.org/10.1016/j.jclepro.2014.01.038.
http://dx.doi.org/10.1016/j.jclepro.2014... , Singh et al. (2016)Singh, S., Olugu, E. U., & Musa, S. N. (2016). Development of sustainable manufacturing decision making models for small and medium enterprises. Procedia CIRP, 40, 608-613. http://dx.doi.org/10.1016/j.procir.2016.01.142.
http://dx.doi.org/10.1016/j.procir.2016.... , Helleno et al. (2017)Helleno, A. L., Moraes, A. J. I., & Simon, T. S. (2017). Integrating sustainability indicators and lean manufacturing to assess manufacturing processes: Application case studies in Brazilian industry. Journal of Cleaner Production, 153, 405-416. http://dx.doi.org/10.1016/j.jclepro.2016.12.072.
http://dx.doi.org/10.1016/j.jclepro.2016... .

Intensity of Importance	Definition	Explanation
1	Equal Importance	Two activities contribute equally to the objective
2	Weak or slight
3	Moderate importance	Experience and judgment slightly favor one task over another
4	Moderate plus
5	Strong importance	Experience and judgment strongly favor one task over another
6	Strong plus
7	Very strong or demonstrated importance	A task is favored very strongly over another; its dominance demonstrated in practice
8	Very, very strong
9	Extreme importance	The evidence favoring one task over another is of the highest possible order of affirmation
Reciprocals of above	If task i has one of the above non-zero numbers assigned to it when compared with task j, then j has the reciprocal value when compared with i	A reasonable assumption
1.1 – 1.9	If the activities are very close	It may be difficult to assign the best value, but when compared with other contrasting activities the size of the small numbers would not be too noticeable, yet they can still indicate the relative importance of the activities.

Specifications	Press A	Press B
Installation year	1989	2012
Model	A2 400-2.6	SAL 400-2.8
Drive type	Flywheel drive
Capacity	4000 kN
Slide stroke	35 mm
Stroking speed	80 – 250 strokes per minute	80 – 400 strokes per minute
Stacking device for laminations	No	Yes
Dynamic mass counterbalance	No	Yes
Area of bolster plate and slide	2600 x 1200 mm	2800 x 1200 mm

Dimension	Aspect	Indicator	Unit	Press A	Press B
Economic	Cost	Maintenance	$/part	0.0132	0.0045
	Cost	Production	$/part	0.0442	0.0103
	Productivity	Production rate	parts/min	100	187
		Setup time	min	64	57
		Operating yield (OEE)	%	44	60
	Quality	Percentage of nonconformance	%	1.89	0.67
	Duties and legislation	Cost of absence and accidents	$/1000 parts	0.2766	0.1471
	Duties and legislation	Replacement cost of scrap	$/1000 parts	0.9627	0.1819
Environmental	Consumption of inputs	Electrical energy	kWh/part	0.0188	0.0113
		Stamping fluid	ml/part	0.2667	0.3200
		Lubricating oils	ml/part	0.0020	0.0005
	Material usage	Filters	units/1 million parts	0.0795	0.0271
	Material usage	Tools	mm/100.000 parts	0.6667	0.7692
	Occupied area	Total	m²	78	105
	Occupied area	Material being processed	m²	19.5	28.5
	Emissions and waste	Quantity of CO₂	g/part	2.0829	1.2558
	Emissions and waste	Non-reused fluids	ml/part	0.2347	0.2880
Social	Intensity of task	Calories burned in operation	qualitative	0.6667	0.3333
	Intensity of task	Calories burned in setup	qualitative	0.5238	0.4762
	Occupational health	Level of noise	dB	106	95
		Ergonomics (setup)	qualitative	0.4762	0.5238
		Ergonomics (operation)	qualitative	0.2500	0.7500
	Worker training and satisfaction	Level of instruction	qualitative	0.4167	0.5833
		Occupational training	hr/operator/year	100	150
		Degree of motivation for the task	qualitative	0.3333	0.6667
	Job safety	Number of accidents	accidents/year	0.0318	0.0135
		Risk of accidents (operation and setup)	qualitative	0.6000	0.4000
		Risk of accidents (maintenance)	qualitative	0.7500	0.2500

Dimension	Weight (dw)	Aspects	Weight (aw)
Economic	1/3	Costs	0.250
		Productivity	0.375
		Quality	0.125
		Guarantees and duties	0.250
Environmental	1/3	Production inputs consumption	0.334
		Material usage	0.222
		Land use	0.222
		Emissions, waste and effluents	0.222
Social	1/3	Labor intensity	0.181
		Occupational health	0.273
		Worker training and satisfaction	0.273
		Job safety	0.273

Dimension	Aspects	Press A	Press B
Economic	Costs	0.1952	0.0548
	Productivity	0.2196	0.1554
	Quality	0.0924	0.0326
	Guarantees and duties	0.1867	0.0633
	Economic value	0.0578	0.0255
Environmental	Production inputs consumption	0.2075	0.1265
	Material usage	0.1343	0.0877
	Land use	0.0924	0.1296
	Emissions, waste and effluents	0.1191	0.1029
	Environmental value	0.0483	0.0382
Social	Labor intensity	0.1077	0.0733
	Occupational health	0.1639	0.1091
	Worker training and satisfaction	0.1684	0.1047
	Job safety	0.1867	0.0863
	Social value	0.0522	0.0311
	SIMO	0.1583	0.0948

Total investment	$ 8,423,000
Press (new)	$ 6,400,000
Taxes and import charges	$ 1,373,000
Transport and commissioning	$ 250,000
Devices and accessories	$ 400,000
Cash savings	$ 160,000 / month
Opportunity cost	1% / month
Company’s payback policy	60 months

Dimension weights (%)			Env + Soc Obsolescence
Economic	Environmental	Social	Env + Soc Obsolescence
80	10	10	11.4%
60	20	20	21.4%
40	30	30	30.2%

Associação Brasileira de Engenharia de Produção Av. Prof. Almeida Prado, Travessa 2, 128 - 2º andar - Room 231, 05508-900 São Paulo - SP - São Paulo - SP - Brazil
E-mail: production@editoracubo.com.br

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Maintenance Costs	Indicator Value (iv) ($/part)	Normalized Indicator Value (niv)
Press A	0.0132	0.7466
Press B	0.0045	0.2534

Production rate	Indicator Value (iv) (parts/min)	Reciprocal Indicator Value (iiv)	Normalized Reciprocal Indicator Value (niv)
Press A	100	0.0100	0.6512
Press B	187	0.0054	0.3488