Closing the gap between planning theory and shop floor reality
Industries nowadays are faced with a number of challenges such as time loss by manually creating and updating production plans and schedules, time loss by fine-tuning schedules via phone or email, inaccessible knowledge locked within planner and team coordinator, number and duration of downtimes due to slower response to unplanned events, difficult management of a diverse product portfolio, long and unpredicted lead times, high intermediate inventory, etc.
Although competitive circumstances in many industries, such as automotive or chemical, already push many production processes to its limits, there are still plenty of possibilities for improvements on an organisational level, which help tackling the challenges mentioned above. Just like Google Maps navigations enables drivers to travel between point A and point B by the most suitable route according to the current situation and predicted road congestions, a production steering solution could guide the production process by its optimal way towards the goal.
Advanced in ubiquitous AI can learn to predict lead times more accurately due to external circumstances, with such an accuracy operational downtimes can be prevented or reduced significantly, allocation of human resources can become more optimized, planners and team coordinators can take advantage of automatic planning options and can dedicate more of their time tasks with higher added value, inventory can be lowered and the solution can help approaching towards the goal of lean manufacturing.
Innovative STAR solutions help improve the already cutting-edge QlectorLEAP product (https://qlector.com/solutions.html), which can save 1 day/week for planners and team coordinators, simulate the production process for several day in advance, enable just-in-time delivery, replace repetitive task with added value tasks, reduce lead times, enable higher turnover ratio, enable on-time preparation of tool changes and finally, increase OEE.