This paper develops operational methods for the minimization of the energy consumption of manufacturing equipment. It is observed that there can be a significant amount of energy savings when non-bottleneck (i.e. underutilized) machines/equipment are turned off when they will be idle for a certain amount of time. Using this fact, several dispatching rules are proposed. A detailed performance analysis indicates that the proposed dispatching rules are effective in decreasing the energy consumption of especially underutilized manufacturing equipment. In addition, a multi-objective mathematical programming model is proposed to minimize the energy consumption and total completion time. Using this approach, a production manager will have a set of non-dominated solutions (i.e. the set of efficient solutions) which he/she can use to determine the most efficient production sequence which will minimize the total energy consumption while optimizing the total completion time.

A great amount of energy is wasted in industry by machines that remain idle due to underutilisation. A way to avoid wasting energy and thus reducing the carbon print of an industrial plant is to consider minimisation of energy consumption objective while making scheduling decisions. To minimise energy consumption, the decision maker has to decide the timing and length of turn off/turn on operation (a setup) and also provide a sequence of jobs that minimises the scheduling objective, assuming that all jobs are not available at the same time. In this paper, a framework to solve a multiobjective optimisation problem that minimises total energy consumption and total tardiness is proposed. Since total tardiness problem with release dates is an NP‐hard problem, a new greedy randomised multiobjective adaptive search metaheuristic is utilised to obtain an approximate pareto front (i.e. an approximate set of non‐dominated solutions). Analytical Hierarchy Process is utilised to determine the ‘best’ alternative among the solutions on the pareto front. The proposed framework is illustrated in a case study. It is shown that a wide variety of dispersed solutions can be obtained via the proposed framework, and as total tardiness decreases, total energy consumption increases.

Appropriate maintenance can prolong the life of an asset and prevent costly breakdowns that may result in lost production, failed shipping schedules and a decline in customer satisfaction. The goal of this study was to present a comprehensive framework that utilises sustainability metrics based on social, environmental and economic criteria to select an appropriate maintenance strategy among a variety of maintenance strategy alternatives, such as preventive, failure-based, reliability-centred, condition-based and total productive maintenance strategies, for a manufacturing company. The sustainability-based approach may significantly influence the personnel, energy, material and the overall costs in a company. In the first step of this paper, a sustainability-based decision-making structure is proposed for the maintenance strategy selection problem applying the concept of factor analysis to determine the leading factors in each of the sustainability pillars. In the next step, a fuzzy VIKOR framework is used to select the most appropriate maintenance strategy. The provided approach is illustrated using a manufacturing industry case study.

High–surface area micro-and nanoscale electrospun fibers were produced for noise-reduction purposes using three different polymers: polyvinylpyrrolidone (PVP), polystyrene (PS), and PVC. These polymers were initially dissolved in appropriate solvents and electrospun at various electrospinning conditions. The two-microphone transfer-function method of the Brüel and Kjær (B&K) impedance tube was used to determine the acoustical properties of the electrospun fibers at different frequencies. Test results showed that the absorption coefficients of the fibers (200 nm to 7 µm) were significantly enhanced at nanoscale. The reason behind this phenomenon may be attributed to the higher surface area of fibers and their interactions with more sound waves/air molecules. Overall, the findings of this research will open up new possibilities for the noise-reduction problem of aircraft, other transportation vehicles, and infrastructures.