LUCKYTEK
Advanced planning and scheduling
Advanced Planning and Scheduling (APS)
Advanced planning and scheduling
Our services bring advanced detailed planning of production and business processes directly to the heart of every company. Supported by a sophisticated platform of optimization technologies based on genetic algorithms using Darwinian mutation, selection and crossover operators, our solution provides you with maximum flexibility to meet the complex requirements of all organizations operating in a highly dynamic environment.
Efficient integration with your already installed systems, rapid analysis of large volumes of data, powerful decision support, event monitoring and real-time back-optimization of plans ensure that we provide you with advanced detailed planning adapted precisely to your unique operational needs.
And above all, with the help of optimization technologies, you can achieve and often exceed your business goals based on the measurement of the main performance parameters of KPIs (Key Performance Indicators) and the improvement of management in critical operational areas. With our powerful detailed advanced planning solution, you can maximize asset utilization, reduce operating costs, increase on-time delivery, reduce manufacturing lead times and much more.
Main advantages and benefits of advanced detailed planning
A sophisticated platform of planning optimization technologies based on genetic algorithms using the Darwinian mutation, selection and crossover operators.
Production capacity planning
Capacity planning is often a juggling act. Finding the ideal balance between customer demands and organizational capacity involves many dynamic factors. Faced with such complexity, many manufacturing enterprises simply resign and use poor-quality resource planning that is based on either unlimited capacities or constrained capacities - essentially ignoring the actual capacity of the firm.
With the right solution using adaptive resource scheduling with limited capacity, you can balance demand and actual resource capacity and avoid underutilization or failure to meet your customers' needs.
The APS system performs collision-free, situation-based planning of custom filling with limited production resources in mind. The APS system guarantees that the execution of orders takes place in real time intervals and that possible deviations are immediately recognized through the continuous comparison of planned and actual values. The APS system contains adaptive planning algorithms (genetic algorithms working on the principle of artificial evolution and Darwinian principles of selection, mutation and crossover) for optimization based on realistic technological procedures.
The result of the planning algorithms is displayed as a Gantt chart for a better overview.
Scheduling algorithms take into account constraints from the customer by orienting the order of scheduled jobs according to the priority, importance of individual customers, or according to the minimization of internal costs. When planning orders, it is also necessary to take into account technological limitations (e.g. adjusting machines for individual types of products) and storage time and related storage costs, where in some cases the savings resulting from optimized machine adjustment are offset by additional storage costs.
What constitutes the optimal sequence of orders depends on many frequently changing factors, but two important aspects are needed when planning any production:
APS uses simulation to calculate and display different situations with regard to variants, quantities and deadlines. Fully automatic production planning is possible for production processes with few restrictive conditions and clear rules. In the case of more complex planning processes, the decision according to which variant will be produced is up to the management of the company.
Years of experience with the analysis of technological procedures show that the entered values (mainly planned times for individual production operations, times for adjustment, cleaning, etc.) deviate significantly from reality. The reason for this is that the input of values takes place at a certain time before the start of production, based on estimates and time studies, and these values are then not refined during production itself. From this follows an important requirement for the APS adaptive planning function: comparing time values from technological procedures and actual production times and subsequently adjusting technological times according to reality, which enables reliable and accurate production planning.
Recording of current production times is done simply and economically using terminals. Current times related to individual orders and products are recorded here. Statistically calculated average values of these actual times can then be compared with times in technological procedures and it is possible to analyze deviations.
Adaptive production planning must deal with the following complexity of assigned constraints, which are often at odds with the planning objective:
For adaptive planning of a larger number of orders in order to guarantee all delivery dates to customers, APS provides the following:
Strategies for adaptive production planning and planning algorithms:
There are different strategies for optimization-based job scheduling. A suitable strategy should be selected according to specific conditions:
Forward planning:
Therefore, if the delivery date for the customer is set in advance, or if it is only possible to deliver on certain dates, e.g. due to the delivered dates from the carrier, back-planning of orders is recommended.
Backward planning:
Planning of individual operations in the technological process.
Scheduling orders on production resources.