Effective monitoring of carbon emissions from industrial sector using statistical process control

The industrial sector is considered one of the fastest-growing sources greenhouse gases, due to excessive consumption energy required cope with growing production exhaustive products. statistical process monitoring (SPM) can be an effective tool for and controlling carbon emissions from industries. This article presents economic-statistical design combined Shewhart X¯ exponentially weighted moving average (EWMA) scheme (X¯&EWMA scheme) industries allow prompt action emissions. parameters proposed SPM have been optimized minimizing expected total cost, including cost operational costs scheme. X¯&EWMA has considering a wide range shifts in mean emission process, ensuring that constraints on inspection rate, sample size, false alarm rate are all satisfied. Comparative studies showed optimal reduced by about 40%, 77%, 28% compared basic X¯, EWMA, schemes, respectively. impact effectiveness also investigated sensitivity analysis. Finally, application demonstrated using real data different facilities. study considerably reduce owing widen literature utilization tools managing quality environment.