PRODUCTION SEQUENCING AND STABILITY ANALYSIS OF A JUST-IN-TIME SYSTEM WITH SEQUENCE DEPENDENT SETUPS

Just-In-Time (JIT) production systems is a popular area for researchers but real-world issues such as sequence dependent setups are often overlooked. This research investigates an approach for determining stability and an approach for mixed product sequencing in production systems with sequence dependent setups and buffer thresholds which signal replenishment of a given buffer. Production systems in this research operate under JIT pull production principles by producing only when demand exists and idle when no demand exists. In the first approach, an iterative method is presented to determine stability for a multi-product production system that operates with replenishment signals and may have sequence dependent setups. In this method, a network of nodes representing machine states and arcs representing the buffer inventory levels is used to find a stable trajectory for the production system via an iterative procedure. The method determines suitable buffer levels for the production system that ensure that a trajectory originating from any point within a buffer region will always map to a point contained on another buffer region for all future mappings. This iterative method for determining the stability of a production system was implemented using an algorithm to calculate the buffer inventory regions for all arcs in a given arc-node network. The algorithm showed favorable results for two and three product systems in which sequence dependent setups may exist. In the second approach, a product sequencing algorithm determines a product sequence for a production system based on system parameters – setup times, buffer levels, usage rates, production rates, etc. The algorithm selects a product by evaluating the goodness of each product that has reached the replenishment threshold at the current time. The algorithm also incorporates a lookahead function that calculates the goodness for some time interval into the future. The lookahead function considers all branches of the tree of potential sequences to prevent the sequence from travelling down a dead-end branch in which the system will be unable to avoid a depleted buffer. The sequencing algorithm allows the user to weight the five terms of the goodness equations (current and lookahead) to control the behavior of the sequence

Neurovascular unit dysfunction with blood-brain barrier hyperpermeability contributes to major depressive disorder: a review of clinical and experimental evidence

About one-third of people with major depressive disorder (MDD) fail at least two antidepressant drug trials at 1 year. Together with clinical and experimental evidence indicating that the pathophysiology of MDD is multifactorial, this observation underscores the importance of elucidating mechanisms beyond monoaminergic dysregulation that can contribute to the genesis and persistence of MDD. Oxidative stress and neuroinflammation are mechanistically linked to the presence of neurovascular dysfunction with blood-brain barrier (BBB) hyperpermeability in selected neurological disorders, such as stroke, epilepsy, multiple sclerosis, traumatic brain injury, and Alzheimer’s disease. In contrast to other major psychiatric disorders, MDD is frequently comorbid with such neurological disorders and constitutes an independent risk factor for morbidity and mortality in disorders characterized by vascular endothelial dysfunction (cardiovascular disease and diabetes mellitus). Oxidative stress and neuroinflammation are implicated in the neurobiology of MDD. More recent evidence links neurovascular dysfunction with BBB hyperpermeability to MDD without neurological comorbidity. We review this emerging literature and present a theoretical integration between these abnormalities to those involving oxidative stress and neuroinflammation in MDD. We discuss our hypothesis that alterations in endothelial nitric oxide levels and endothelial nitric oxide synthase uncoupling are central mechanistic links in this regard. Understanding the contribution of neurovascular dysfunction with BBB hyperpermeability to the pathophysiology of MDD may help to identify novel therapeutic and preventative approaches