Investigating the impact of social sustainability within maintenance operations

Abstract

Purpose – The purpose of this paper is to primarily focus on labor in maintenance areas, addressing human rights issues, labor standards and safety standards. The main issue is to investigate how these factors are considered to drive the prioritization of maintenance interventions within maintenance plans. In particular, a method for criticality analysis of production equipment is proposed considering specific labor issues like age and gender, which can be useful to steer maintenance plans toward a more social perspective. Design/methodology/approach – The authors focus on the two main social issues of SA 8000 norms, age and gender, exploring how these issues may drive the selection of maintenance policies and the relative maintenance plans. The research is conducted through fuzzy analytical hierarchy process (AHP) implemented within a failure mode effects analysis (FMEA). Findings – The research is conducted through fuzzy AHP implemented within a FMEA. The maintenance plans resulting from the FMEA driven by social issues are evaluated by a benchmark of three different scenarios. The results obtained allowed the firm to evaluate maintenance plans, considering the impact on workers’ health and safety, the environment, social issues like gender and age. Research limitations/implications – One of the main limitation of this research is that it should also encompass maintenance costs under social and safety perspective. The method developed should be extended by further study of maintenance planning decisions subject to budget constraints. Moreover, it would be worth evaluating the effect of adopting more proactive maintenance policies aimed at improving plant maintainability in view of what emerged during the test case in the presence of an aged workforce and the subsequent need to prevent and/or protect people from hidden risks. Practical implications – With reference to the results obtained from the two models of this scenario, the authors observed an increase of equipment criticality, from B class to the A class, and similarly from C class to B class. No equipment has reduced its criticality. This depends on the particular context and the relative weights of drivers indicated in its AHP matrixes. Social implications – The paper addressed the main social implication as well as other social issues represented by age and gender factors, which are normally neglected. The Action Research (AR) proved the effects resulted from considering either gender factor or gender and age factors at the same time for maintenance policy selection. All in all, an increase of criticality is evident even if “people” is a driver with less importance than “environment” and “structures.” Originality/value – The present work focussed on a new definition of a criticality ranking model to assign a maintenance policy to each component based on workers’ know-how and on their status. The approach is conceived by the application of a fuzzy logic structure and AHP to overcome uncertainties, which can rise during a decision process when there is a need to evaluate many criteria, ranging from economic to environmental and social dimensions.

Exploring the impacts and contributions of maintenance function for sustainable manufacturing

“…For example, Ajukumar and Gandhi (2013) proposed an evaluation model for equipment design that includes maintenance requirements related to environmental considerations. Savino, Macchi, and Mazza (2015) propose a ranking model to assign maintenance policies by considering social issues related to age and gender and workers' know-how. Ighravwe and Oke (2017) used environmental factors in their ranking method that were obtained from waste management, health and safety, and environmental management literatures, as they report lack of defined factors on the impact of maintenance on the natural environment in maintenance literature.…”

The concept of maintenance sustainability performance assessment by integrating balanced scorecard with non-additive fuzzy integral

“…planning service activities, monitoring the condition of machines and devices, it enables reduction of consumption of technological media, raw materials and materials, as well as their more efficient use [1,3,27,29,30,52]. The social dimension concerns the relationship between the maintenance function and its stakeholders both within the company and outside of it, with particular emphasis on the employees of the technical department, production, suppliers of spare parts, service providers, etc., competence and satisfaction of employees, work environment [4,48], satisfaction. Moreover, by preventing emergency events and limiting their consequences, maintenance is related to the safety of processes and people [43].…”

Ordered weighted aggregation of fuzzy similarity relations and its application to detecting water treatment plant malfunction

“…Environmental performance has become a critical and general issue in human society [22,48,49]. Creating and maintaining robust environmental indicators is essential when complex environmental quality factors need to be effectively exploited in developing and communicating environmental public policy [23,50]. For instance, a poorly maintained industrial water treatment plant can significantly degrade the environmental performance [51].…”