A fuzzy framework for sustainability in manufacturing
Balancing people and profit, a framework tool developed at Khalifa University supports project managers to take decisions underpinned by sustainability.
Every day, project managers in manufacturing face a balancing act. They must constantly weigh competing priorities such as cost, efficiency, environmental impact and of course the human factors before choosing the most sustainable production method. What if there was a way to model their situation and help them select optimal solutions?
Current decision-making models can only handle one set of factors at a time.
To address this limitation, Vikas Swarnakar, Raed Jaradat and Malik Khalfan at the Management Science and Engineering department at Khalifa University and co-workers have built a two-stage sustainable project selection framework designed to optimize choices for sustainability. Their framework is the first to consider economic, social, and environmental factors all at once, and can be adapted for any industry setting.
“Until recently, most companies considered economic factors when optimizing production lines,” says Swarnakar. “It is only within the last decade that industries have begun incorporating social and environmental factors into their decision-making processes.”
“Stakeholders in industry are very keen to ensure that sustainability factors are ranked highly, to meet manufacturing regulations and wider global targets.”
Vikas Swarnakar
Inspiration for the framework stemmed from Swarnakar’s own experience of project management at an automotive component manufacturer in India. The company, which had five different production lines making automotive engine valves, struggled to meet its sustainability goals. All the lines were plagued by defects and sustainability-related concerns.
Swarnakar recognized that refining such production lines for optimal sustainability would require rapid assessment of social, environmental and economic factors. Each company using the tool would have a different set of priorities. The complexity of these decisions would require a structured model capable of handling multiple factors at once.
“I suggested that we could build a sustainability-based decision-making model that would select the optimal production line for the engine valves,” says Swarnakar. “This challenge became the first case study for our framework.”
To enable this simultaneous analysis, the team combined two models: the fuzzy Kano model and a fuzzy interference system. “The fuzzy Kano model allows us to sort factors into five different categories and rank them in order of importance to the stakeholders,” says Swarnakar. “Stakeholders in industry are very keen to ensure that sustainability factors are ranked highly, to meet manufacturing regulations and wider global targets.”
The factors were selected through a questionnaire and panel discussion with key stakeholders and industry experts at the Indian company. The participants considered a wide range of factors—initial costs, air quality, resource management and local employment opportunities—and graded them according to importance. The panel selected 19 factors in the highest ‘must-be’ category: six economic, six environmental, and seven social.
“With the fuzzy interference system, there is no limit to the number of factors that can be applied to make a decision, which is very useful,” says Swarnakar.
“The pivotal emphasis on stakeholder input is a unique feature of our framework,” adds Jaradat. “No other decision-making models prioritize the stakeholders’ wishes and specific business requirements in this way.”
Using the stakeholder-selected sustainability criteria, the team ran the framework to identify the optimal lines to improve the sustainability performance of manufacturing engine valves. The results improved accuracy and reliability in production lines, with sustainability underpinning every production decision.
Swarnakar and Khalfan are now taking the concept further. They’re developing a structured framework to implement in construction and demolition waste management in the United Arab Emirates. Their work aligns directly with the UAE national sustainability goals for achieving net zero and diversifying the economy. “We will continually adapt our model to meet current and future challenges,” says Swarnakar.
“Our framework can be applied to any industry. We set the factors based on the stakeholders’ requirements, and then identify optimal solutions,” Jaradat explains.
Reference
Swarnakar, V.; Jaradat, R.; Khalfan, M.; Maalouf, M.; Eltoukhy, A.E.E.; & Hossain, N.U.I. Sustainable project choice: Integrating must-be kano and fuzzy logic for optimal project selection. Journal of Open Innovation: Technology, Market, and Complexity 11 (2025) | Article
