Preventive maintenance model for heating ventilation air conditioning in pharmacy manufacturing sector

One of the most important factors for the success of maintenance system in heating, ventilation, and air conditioning (HVAC) implementation is satisfaction rate of preventive maintenance. However, there is only few research available regarding the factors influence in the success of maintenance system in manufacturing facilities, including HVAC. The study unearths the complexity link by using the Preventive Maintenance Satisfaction Model, specifically constructed for this study by combining four external factors and two internal factors to evaluate the implementation of the preventive maintenance system in the pharmacy manufacturing industries. The Indonesia pharmacy manufacturing is selected as a case study. The Structural Equation Modeling approach is applied in the analysis phase. Four factors are explored in this evaluation, tools, duration, rate of skill competency, and rate of machine complexity. The analysis results indicated that all factors positively influenced the rate of preventive maintenance satisfaction through facilitating conditions (β = 0.566, p  < 0.001). The significant contribution of this research is to develop methodologically factors of the satisfaction rate of preventive maintenance in terms of HVAC maintenance system in manufacturing, supporting company sustainability programs. This study gives valuable insights to decision-makers involved in the implementation and development of maintenance system.

[1]  Viswanath Venkatesh,et al.  Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead , 2016, J. Assoc. Inf. Syst..

[2]  D. Q. Nguyen,et al.  The essential skills and attributes of an engineer: a comparative study of academics, industry personnel and engineering students , 1998 .

[3]  Ander Ibarloza,et al.  Contribution to Energy Management of the Main Standards for Environmental Management Systems: The Case of ISO 14001 and EMAS , 2017 .

[4]  Choesnul Jaqin,et al.  Integration of nominal group technique, Shainin system and DMAIC methods to reduce defective products: A case study of tire manufacturing industry in Indonesia , 2019, Management Science Letters.

[5]  B. Jiang,et al.  The Investigation of Consumers’ Behavior Intention in Using Green Skincare Products: A Pro-Environmental Behavior Model Approach , 2018, Sustainability.

[6]  C. Bhat,et al.  An Exploration of the Relationship between Timing and Duration of Maintenance Activities , 2004 .

[7]  L. Cronbach.  Coefficient alpha and the internal structure of tests , 1951 .

[8]  Chih-Hsing Chu,et al.  Exploring the influential factors of manufacturers’ initial intention in applying for the green mark ecolabel in Taiwan , 2015 .

[9]  Nick von Tunzelmann,et al.  Industry-specific competencies and converging technological systems: evidence from patents , 2001 .

[10]  Gonçalo Marques,et al.  An Indoor Monitoring System for Ambient Assisted Living Based on Internet of Things Architecture , 2016, International journal of environmental research and public health.

[11]  Michael Mannino,et al.  Information technology acceptance in the internal audit profession: Impact of technology features and complexity , 2009, Int. J. Account. Inf. Syst..

[12]  Gordon Lowry,et al.  Modelling user acceptance of building management systems , 2002 .

[14]  Jacky Chin,et al.  A Behavioral Model of Managerial Perspectives Regarding Technology Acceptance in Building Energy Management Systems , 2016 .

[15]  M. Tutino,et al.  Discontinuous and Continuous Indoor Air Quality Monitoring in Homes with Fireplaces or Wood Stoves as Heating System , 2015, International journal of environmental research and public health.

[16]  Nauman Ahmad Zaffar,et al.  Smart meters for industrial energy conservation and efficiency optimization in Pakistan: Scope, technology and applications , 2015 .

[17]  Andrew M. Farrell,et al.  Factor analysis and discriminant validity:a brief review of some practical issues , 2009 .

[18]  Hyojoo Son,et al.  Toward an understanding of construction professionals' acceptance of mobile computing devices in South Korea: An extension of the technology acceptance model , 2012 .

[19]  Jacky Chin,et al.  Investigating Users’ Perspectives in Building Energy Management System with an Extension of Technology Acceptance Model: A Case Study in Indonesian Manufacturing Companies☆ , 2015 .

[20]  Rune Prytz,et al.  Machine learning methods for vehicle predictive maintenance using off-board and on-board data , 2014 .

[21]  Peter Trkman,et al.  Analyzing older users' home telehealth services acceptance behavior - applying an Extended UTAUT model , 2016, Int. J. Medical Informatics.

[22]  A. Dalmazzo.  Technological Complexity, Wage Differentials and Unemployment , 2002 .

[23]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[24]  Michael R. Mullen,et al.  Structural equation modelling: guidelines for determining model fit , 2008 .

[25]  Reny Nadlifatin,et al.  A study of student behavior in accepting the Blackboard Learning System: A Technology Acceptance Model (TAM) approach , 2014, Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

[26]  Micaela Demichela,et al.  Using Field Data for Energy Efficiency Based on Maintenance and Operational Optimisation. A Step towards PHM in Process Plants , 2018 .

[27]  B. Jiang,et al.  Understanding the Consumers’ Behavior Intention in Using Green Ecolabel Product through Pro-Environmental Planned Behavior Model in Developing and Developed Regions: Lessons Learned from Taiwan and Indonesia , 2018 .

[28]  Markus Dwiyanto Tobi Sogen,et al.  Mobile Based Android Application Pharmaceutical Dictionary with Direct Search as Searching Process , 2019 .

[29]  Satria Fadil Persada,et al.  Safety-Culture Exploration in Taiwan’s Metal Industries: Identifying the Workers’ Background Influence on Safety Climate , 2017 .

[30]  Jui-Sheng Chou,et al.  Smart meter adoption and deployment strategy for residential buildings in Indonesia , 2014 .