Using problem-oriented monitoring to simultaneously improve productivity and environmental performance in manufacturing companies

ABSTRACT

Nowadays companies are trying to become ‘greener’, which requires integrating the environmental dimension into their traditional performance metrics. However, managers may not have the complete information and data for their environmental problems and, crucially, there is a lack of knowledge about how these environmental issues affect a company’s productivity. Even though the availability of technology has increased and it is easier than ever to obtain all kinds of data, there is a lack of agreement on how to correctly measure environmental performance, and companies could suffer from an overload of environmental information. The biggest challenge, therefore, lies in how to measure and obtain the appropriate environmental data and how to interpret and relate these data to the company’s productivity. In this context, this paper presents a new and innovative approach, called Plug&Glean, for diagnosing and improving productivity and environmental performance in a defined production system. The approach is applied to a case study in the north of Spain. The findings suggest that it is possible to improve productivity and environmental performance at the same time, as well as reinforce the notion that waste elimination has a positive impact on improving environmental performance.

KEYWORDS:

• Industry 4.0
• easy-to-use monitoring
• lean-green
• productivity
• environmental sustainability

Acknowledgements

The work presented in this paper was carried out within the framework of the LIFE MCUBO research project funded by the European Union (LIFE15 ENV/ES/000379), through the LIFE programme. In addition, the authors would like to acknowledge the support received from AdP, the Special Patrimonial Fund at Universidad de La Sabana and the doctoral grant from TECNUN Escuela de Ingenieros, Universidad de Navarra. We also thank the editor and anonymous reviewers for their useful comments and insights.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work presented in this paper was carried out within the framework of the LIFE MCUBO research project funded by the European Union [LIFE15 ENV/ES/000379], through the LIFE programme.