Abstract
The textile industry is a complicated manufacturing industry because it is a fragmented and heterogeneous sector dominated by Small and Medium Enterprises (SMEs). There are various energy-efficiency opportunities that exist in every textile plant. However, even cost-effective options often are not implemented in textile plants mostly because of limited information on how to implement energy-efficiency measures. This paper presents the expansion of problem formulation of consummation management based on load shifting in textile industry. The mathematical model is a Non Polynomial (NP) hard optimization problem to determine the start time of the process in order to minimize the total electricity cost under varying tariffs such as flat rate and Time of Use (TOU). For solve this problem, Ant Colony Optimization (ACO) is applied and compared with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). To show its efficiency, the case studies in case of Single Process Multiple Jobs (SPMJ) in term of small, medium and large scales are demonstrated. The results show that the proposed method is able to achieve the best solution efficiently and easy to implement.
Highlights
The textile industry is one of the most convoluted contemporary industries because it is a fragmented and heterogeneous sector dominated by Small and Medium Enterprises (SMEs)
The case studies in case of Single Process Multiple Jobs (SPMJ) are studied
In order to demonstrate the efficiency of the Ant Colony Optimization (ACO) method, the distribution outlines of the best solution of each trial are considered
Summary
The textile industry is one of the most convoluted contemporary industries because it is a fragmented and heterogeneous sector dominated by Small and Medium Enterprises (SMEs). Electrical energy is one of the main cost factors in the textile industry. In times of high energy price volatility, improving energyefficiency should be a primary concern for textile plants. There are various energy-efficiency opportunities that exist in every textile plant, many of which are costeffective. Know-how on energy-efficiency technologies and practices should, be prepared and disseminated to textile plants. An extensive literature review was conducted in this study to collect information on the energy use in and energy efficiency measures/technologies for the textile industry (Ashok and Banerjee, 2000). LM is the strategies, reported with potential reduction in system peak demand with different LM (Sheen et al, 1994). Many the utility, have the reduction in peak demand improves the utilization of base load generating stations and avoids costly peaking stations
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