Continuous Process Improvement Implementation Framework Using Multi-Objective Genetic Algorithms and Discrete Event Simulation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose Continuous process improvement is a hard problem, especially in high variety/low volume environments due to the complex interrelationships between processes. The purpose of this paper is to address the process improvement issues by simultaneously investigating the job sequencing and buffer size optimization problems. Design/methodology/approach This paper proposes a continuous process improvement implementation framework using a modified genetic algorithm (GA) and discrete event simulation to achieve multi-objective optimization. The proposed combinatorial optimization module combines the problem of job sequencing and buffer size optimization under a generic process improvement framework, where lead time and total inventory holding cost are used as two combinatorial optimization objectives. The proposed approach uses the discrete event simulation to mimic the manufacturing environment, the constraints imposed by the real environment and the different levels of variability associated with the resources. Findings Compared to existing evolutionary algorithm-based methods, the proposed framework considers the interrelationship between succeeding and preceding processes and the variability induced by both job sequence and buffer size problems on each other. A computational analysis shows significant improvement by applying the proposed framework. Originality/value Significant body of work exists in the area of continuous process improvement, discrete event simulation and GAs, a little work has been found where GAs and discrete event simulation are used together to implement continuous process improvement as an iterative approach. Also, a modified GA simultaneously addresses the job sequencing and buffer size optimization problems by considering the interrelationships and the effect of variability due to both on each other

Detection of super-high-frequency partial discharge by using neural networks

A system has been developed for the detection of super-high-frequency (SHF) partial discharge (PD) at frequencies up to 6 GHz. The system consists of three antennas for capturing PDs and a fast digital oscilloscope for sampling data. One of the antennas is a disk-cone antenna with frequency range below 710 MHz. The other two half TEM horn antennas have been designed and constructed for the frequency range 716 MHz - 5 GHz. To extend the frequency range up to 6 GHz, a methodology has been developed by compensating amplitude-response to frequency-magnitude. The compensation is realised by using multilayer feed-forward neural networks to equalise on amplitude-response. A direct sampling method is used to log the captured PD data. This PD detection system has been implemented to measure PDs at a 400 kV electrical substation (Strathaven, Scottish Power Ltd)

Biodiesel production from Cannabis sativa oil from Pakistan

The present study was appraised using response surface methodology for process optimization owing to strong interaction of reaction variables: NaOCH3 catalyst concentration (0.25–1.50%), methanol/oil molar ratio (3:1–9:1), reaction time (30–90 min), and reaction temperature (45–65°C). The quadratic polynomial equation was determined using response surface methodology for predicting optimum methyl esters yield from Cannabis sativa oil. The analysis of variance results indicated that molar ratio and reaction temperature were the key factors that appreciably influence the yield of Cannabis sativa oil methyl esters. The significant (p < 0.0001) variable interaction between molar ratio × catalyst concentration and reaction time × molar ratio was observed, which mostly affect the Cannabis sativa oil methyl esters yield. The optimum Cannabis sativa oil methyl esters yield, i.e., 86.01% was gained at 53°C reaction temperature, 7.5:1 methanol/oil molar ratio, 65 min reaction time, and 0.80% catalyst concentration. The results depicted a linear relationship between observed and predicted values. The residual analysis predicted the appropriateness of the central composite design. The Cannabis sativa oil methyl esters, analyzed by gas chromatography, elucidated six fatty acid methyl esters (linoleic, α-linolenic, oleic, palmitic, stearic, and γ-linolenic acids). In addition, the fuel properties, such as kinematic viscosity at 40°C; cetane number; acid value; flash point; cloud, pour, and cold filter plugging points; ash content; density; and sulphur content, of Cannabis sativa oil methyl esters were evaluated and discussed with reference to ASTM D 6751 and EU 14214 biodiesel specifications

Ogbu and the debate on educational achievement: an exploration of the links between education, migration, identity and belonging

This paper looks at some of the issues raised by Ogbu’s work in relation to the education of different minority ethnic groups. Ogbu poses questions such as the value attached to education, its links to the future and its measurable outcomes in terms of ‘success’ as experienced by black participants. The desire for better life chances leads families to consider migration to a new country or resettlement within the same country, thus making migration both a local and a global phenomenon. As an example, attention is drawn to the situation facing South Asian children and their families in the UK. In terms of ethnicity and belonging, the wider question that is significant for many countries in the West after ‘Nine-Eleven’ is the education of Muslim children. A consideration of this current situation throws Ogbu’s identification of ‘autonomous minority’ into question. It is argued that a greater understanding of diverse needs has to be accompanied by a concerted effort to confront racism and intolerance in schools and in society, thus enabling all communities to make a useful contribution and to avoid the ‘risk’ of failure and disenchantment

A GABAergic projection from the centromedial nuclei of the amygdala to ventromedial prefrontal cortex modulates reward behavior

The neural circuitry underlying mammalian reward behaviors involves several distinct nuclei throughout the brain. It is widely accepted that the midbrain dopamine (DA) neurons are critical for the reward-related behaviors. Recent studies have shown that the centromedial nucleus of the amygdala (CeMA) has a distinct role in regulating reward-related behaviors. However, the CeMA and ventromedial PFC (vmPFC) interaction in reward regulation remains poorly understood. Here, we identify and dissect a GABAergic projection that originates in the CeMA and terminates in the vmPFC (VGat-Cre(CeMA-vmPFC)) using viral-vector-mediated, cell-type-specific optogenetic techniques in mice. Pathway-specific optogenetic activation of the VGat-Cre(CeMA-vmPFC) circuit in awake, behaving animals produced a positive, reward-like phenotype in real-time place preference and increased locomotor activity in open-field testing. In sucrose operant conditioning, the photoactivation of these terminals increased nose-poking effort with no effect on licking behavior and robustly facilitated the extinction of operant behavior. However, photoactivation of these terminals did not induce self-stimulation in the absence of an external reward. The results described here suggest that the VGat-Cre(CeMA-vmPFC) projection acts to modulate existing reward-related behaviors. SIGNIFICANCE STATEMENT Many studies have shown that the interactions between the centromedial nucleus of the amygdala (CeMA) and ventromedial PFC (vmPFC) have critical roles for emotional regulation. However, most studies have associated this circuit with fear and anxiety behaviors and emphasized top-down processing from vmPFC to CeMA. Here, we provide new evidence for bottom-up CeMA to vmPFC influence on reward-related behaviors. Although previous work implicated the CeMA in incentive salience, our results isolate the investigation to a specific CeMA GABAergic projection to the vmPFC. This long-range GABAergic interaction between amygdala and frontal cortex adds a new dimension to the complex regulation of reward-related behaviors