An investigation into minimising total energy consumption and total weighted tardiness in job shops

Learning on Lean Production: A Review of Opinion and Research within Environmental Constraints

“…For this particular parameter, the framework consisting functionalism as well as the fundamental humanism and structuralism was employed, and based on these research approaches the reviewed studies are categorized as below: Liu et al (2014) developed a non-dominant sorting genetic algorithm to attain Pareto front and to diminish total non-processing electricity consumption as well as the total weighted delay in a job shop; Ahemad et al (2013) highlighted the weak areas as potential for company to improve green manufacturing execution through case study in Indian steel industry; Elsayed et al (2013) discussed a 3-step approach for proactive performance assessment of green-lean through case study in an automotive, resulting 10.8% drop in production cost; Salleh et al (2012) studied the green lean total quality information management system via questionnaire in 30 automotive vendors in Malaysia; Esmer et al (2010) intended to find out the optimal number of handling equipment & reduced the ecological harm of Turkish container terminal via a simulation model; Abdulmalek and Rajgopal (2007) applied the value stream mapping (VSM) & simulation model to contrast the before & after state in an integrated steel mill; Purvis et al (2014) explored the flexibility in context of lean, agile & leagile supply networks and investigated the vendor & sourcing flexibility in two UK based specialist fashion retailers; Vivek and Ravindran (2008) emphasized the impact of environmental uncertainty on the lean practices followed by small manufacturing firms; Satao et al (2012) reviewed on how green manufacturing can be achieved through lean in order to prevent pollution & protect environment. Roosen and Pons (2013) offered a method to integrate environmental waste into lean through VSM in manufacturing setting for carbon footprint; Omer (2008) reviewed the literature on energy sources, environment & sustainable development for reducing fossil energy use and to promote the green energies in construction sector; Venkat and Wakeland (2006) investigated the environmental performance for CO 2 emissions using simulation model and suggested that it is quite possible for lean & green to be in clash that leads to tradeoffs and further chances for optimization; Hibadullah et al (2013) explored the relationship between lean and environmental performance in Malaysian automotive industry by structural equation modelling (SEM); Yang et al (2010) hypothesized that environmental management is partially an extension of advanced manufacturing practices and found that the electronic & electrical industries in China & Taiwan have developed their own practices; Herron and Hicks (2008) disseminated the selected lean techniques in companies of north-east England to improve productivity and obtained the savings as eight times greater than total costs from 15 companies; …”

An Energy-Saving Optimization Method of Dynamic Scheduling for Disassembly Line

“…Dai et al [28] proposed an improved genetic-simulated annealing algorithm for flexible flow shop scheduling in order to trade-off between makespan and energy consumption. Liu et al [29] established a scheduling method with the objectives of energy consumption and weighted tardiness. Tang et al [30] proposed an improved particle swarm optimization algorithm for solving the dynamic flexible flow shop scheduling problem.…”

Minimising the energy consumption of tool change and tool path of machining by sequencing the features

“…The swap mutation is adopted as the mutation operator which means two arbitrary genes of a chro-20 mosome are selected and swap the values [45] Fig. 6.…”