Traditional production planning and scheduling systems use a cascade method to allocate materials and production capacity. This approach is easy to use when there is no need for change in planning. However, the need for additional production demands on production lines, resource capacity, or the need to include changes in material availability in planning makes the use of this method difficult. Since the traditional planning, method plans materials and capacity separately, and many systems fail to consistently consider material or capacity constraints, the established scheduling results in plans that are not viable. The emergence of MSF APS is aimed at eliminating this deficiency. By combining all production functions with a management philosophy, production planning with instantaneous data constitutes the main function of MSF APS.
MSF APS Functions
MSF Advanced Planning System (APS) consists of three main functions: Real-Time Production Monitoring, Production Auto-Schedule, and Labour Auto-Schedule Functions.
The production environment on the shop floor can be observed production changes in real-time like machine status and material details. MSF real-time monitoring shows all production processes that can be monitored by way of dynamic real-time systems that collect and process the complete range of production-related data such as quantities, process parameters, and plant and machine status.
MSF auto-schedule functions in case of unacceptable deviations or discrepancies, corrective steps which may include MSF input, are automatically executed. Depending on the degree of automation, data can be directly transferred to subordinate systems. MSF labor auto schedule is a process of the operation data that is transferred to the system and an artificial intelligence algorithm decides the number of people to be assigned to the relevant operation.
MSF APS Components:
MSF APS has a fully autonomous system, which uses the following components to do so.
Coordination of Purchase and Production Orders:
The amount of material at hand must be coordinated in such a way that the amount of material sufficient for production does not waste the production capacity. The MSF APS algorithm ensures that the materials to be used in production orders are reserved for the relevant order, and the remaining available materials are allocated to other orders, respectively. This process is coordinated instantaneously, from purchasing to the finalization of production.
In scheduling inventory by assignment to jobs, the availability of materials is designed to automatically activate the system, as MSF APS initiates the planning even before purchasing. When the goods arrive at the factory, this goods movement is directly related to the reservation on the back, so when MSF APS receives information about the confirmation of the goods movement, it checks all relevant departments and the work order, indicating that the reservation is ready for scheduling. Thus, the inventory information is automatically scheduled to the work orders. The reservation information is also updated in the work order information, and it turns into a status of ready to start production.
Gantt Drag and Drop
Drag-and-drop scheduling has made it much easier to create production schedules in production today. It is a useful application that allows all jobs to start at the desired time in the production timeline or be moved by dragging them to the desired point. This is done by holding and releasing the relevant job with the mouse on the schedule created for this process. When this is done, MSF APS automatically has all the work orders, priorities, reservations, and production capacity schedules ready in a few seconds according to the status in the last modified timeline. As a Gantt chart, the display of reordering the work orders is provided. Thus, its interaction with other work orders is also shown.
Finite Capacity Planning
Finite capacity planning means planning and scheduling by assuming that the enterprise has a certain amount of available resources in production and staying within these resource constraints. MSF APS considers all resources, people, all means of production as constraints in planning and uses these constraints while planning capacity. With the MSF advanced planning algorithm, constraints and objectives in the application are set according to the factory production strategy, planning is started with all capacity data. How much of the capacity is desired to be used in planning is also entered into the objectives. This planning approach ensures the most appropriate and efficient use of limited resource capacity to be applied to product or service production in factories. By using the machines or business centres at the desired capacity and using the resources effectively without overloading, it increases the production and thus creates added value, and increases it to the maximum income level.
Multi-plant collaboration requires the execution of production plans of hierarchically integrated facilities produced in different regions. This coordinated execution further complicates the planning of highly complex operations in a multi-site production environment. MSF APS can overcome this problem with software that aims to efficiently coordinate the production process of various manufacturing facilities under the hierarchical supply chain structure. On this capability, MSF APS collaborates with all plants and coordinates with each other to minimize related costs, shorten order production flow time, etc. such as to get better performance for the entire network. To do this, a genetic algorithm-based heuristic approach is used. The goal is to analyse machines and sequences of operations in multi-site factories to create an optimal timeline for optimizing by reducing overall latency.
Changeover time is the non-production time between the end product of a particular production model and the first good product of another particular model. Changes in materials, equipment, and settlements during this period are non-value-added activities, but they are activities that must be done. MSF APS ensures that the produced materials are planned for the most appropriate time and machine production by optimizing for the most suitable and rapid changeover time for the current production of machinery and work centres.
It is very difficult, but not impossible, for them to produce various products in a single production system in order to dynamically fulfil customer needs in production and without increasing production costs, and even reducing costs if possible, thus ensuring speed and uninterrupted production. Operations such as tool changes and adjustments require additional time and resources, especially when a production area moves from one product to another, especially while often operating in a time-efficient mode. Thanks to the data obtained from the digitized production processes thanks to the MSF software, it is possible to continue working with high efficiency and to save cost and time by reducing the production change. In this planning, real-time re-planning such as combining work orders and dynamically increasing the number of products can be done easily by using genetic algorithms. Thus, it makes an important contribution to increasing the production efficiency of the factory
Merging Independent Work Orders With Each Other
There may be a scheduled order that has been converted to some products. Production may be made for different order quantities and orders in different planned orders. These orders can be merged with another independent work order. Thus, if it is desired to combine this independent order with another existing order, it is possible to do this easily in MSF APS.
When a multi-level BOM is used in production, the production locations in the product’s product tree may differ. In this case, the same job can be produced on the same machine in different single work orders, but including different work orders. Thus, more efficient production is realized by saving machine set-up time and additional material transfer during a job change
Forecasting is a process in which past and present data are used and trends are analyzed to make predictions for the future. It is looking ahead using different forecasting methods and trying to determine future trends and events from today and how they will affect production. It is possible to overcome the problem of future uncertainties by making use of the more realistic intelligible data trends obtained by MSF APS software. Forecasting is done with numerical data from the past by using different analysis methods using quantitative forecasting methods. The forecast here is used in future planning and contributes positively to the success of the plan. This forecast takes into account the facts of the factory’s previous and current performance.
In order for the forecasts to be made correctly, how well the production amount meets the real demand and how well the company’s performance can meet this demand depends on the inclusion of accurate data in the calculations. If the production is very low with the data obtained all the time, that is, if the capacity is low, the forecasts reveal that the production will not be able to meet the demand. Due to this, the dissatisfaction of customers causes negative effects on sales. Excess capacity affects production, and storage problems, and thus increases costs. Both situations have the effect of reducing the profitability of the factory. Accurate estimation leads to the conclusion of the process with sufficient and correct production. MSF software makes these estimations correctly, and the correct data in production ensures that the trends in the capacity and performance of the machines and employees are constantly monitored, the obtained data is data mining in a large pool of information, and the future is predicted correctly. Thus, it contributes to taking a real step into the future with past trends.
Shift Targeted Production
With MSF automatic monitoring system, production is monitored instantly in all shifts, and this calculated data is displayed via panel PC in real-time. Here, by displaying the planned quantity, machine and employee performance, and downtime, it creates a triggering positive effect on employees in real-time. This acts as a trigger to achieve the shift target.
Without digitization, employees in legacy productions do not know what the production target is for their shift or how they currently stand to meet it. They start their shift without a goal. At the end of the shift, they leave their jobs without knowing what was lost. If employees cannot receive this information quickly and accurately, they can instantly monitor their own performance and what the product should be, through the interactive panel, thanks to the digitization offered by MSF. Thus, employees can motivate themselves in a positive way by seeing what they will do and do in their shifts. This adds value as a factor that increases the production of the factory.
Job Assignment Based On Employee Skill Matrix
It is the need of every factory to assign tasks to employees according to their skills. However, finding which job is suitable for whom is very difficult. That’s what the skills matrix does and it’s a table that uses the skills and levels of workers to assign them to the appropriate job in their production planning. MSF APS is used to plan and manage workers’ current skills, roles, and related production projects. These tables allow planning of the most suitable employee for the most suitable job by constantly taking into account in the planning.
The skill matrix helps evaluate the skills needed to employ the best employee in production in the most appropriate workplace. Knowing these skill matrices can help redistribute internal crafting abilities where they are most needed. For this purpose, MSF software collects employee data in addition to the data received from the machines in real-time production data. It plans the most suitable employee for the most suitable job with the data collected in accordance with his authority in the created skill matrices. In accordance with the production strategy of the factory management, it prevents the confusion of authority by enabling only the authorized employee to make this change dynamically in the needs such as changing the priorities in production, changing the order of the sequential works planned accordingly, when necessary.
Real-time Planning With MES
Today, it is the acquisition and use of real-time data that creates a big change by increasing efficiency and productivity in the manufacturing industry. The MSF digital solution has been developed to capture real-time data for every role and process in production, from the production floor to top management, and process it to optimize capacity and transform it into the most efficient production.
With MSF MES, businesses can track and monitor all production orders and operations in real-time, create production orders, split orders or processes, and support worker inputs/outputs. This data can be used as reconfigurable dialogs and kanban visual outputs. The widely used kanban, also available in MSF MES, is a visual method for controlling production as part of lean manufacturing in real-time that shows the system what and when to produce. These obtained data from the input of MSF APS. Thus, it is possible to create real-time production plans with real-time data. It enables this setup, which is created by the digitization of all relevant areas of the system, to turn into real-time planning.
Planning of Maintenance and Production Together
To plan the maintenance in a way that will affect the production the least, it should be included in the factory production calendar and schedules, and attention should be paid to the production plans so that they cannot be used during machine maintenance periods. Otherwise, production or maintenance will be disrupted, and machine health or delivery date will be at risk. To avoid this, MSF software considers maintenance schedules as constraints on the factory schedule and production schedule. In order not to interrupt the production during these periods, it ensures optimum planning by the determined constraints such as shifting the production to another machine, making the production in another production line. It also keeps the machine, whose maintenance is completed, ready to be included in production again for real-time work planning.
In order to make a partnership between maintenance and production successful, factories must have the infrastructure to ensure accessible good communication and cooperation. Thanks to the data obtained with this appropriate digitalized communication, maintenance errors or production interruptions are instantly detected, and the problem is resolved with the opened notifications. By making the repair, the machine is returned to production, and the data collected by measuring the performance of the maintenance are taken into account in the next plan. For the health of the machine, which has an important place in planning at MSF, data such as trends obtained from sensors and predictive or planned maintenance practices and frequency of failures are collected. In this light, the production planning is made in accordance with the date of the machines’ readiness for operation in the factory calendar. In addition, executing daily preventive maintenance on a regular schedule helps reduce costly plant downtime. Genetic algorithms are widely used in MSF, allowing well-coordinated planning and execution workflows.
If there is a step determined in a project as a milestone, this date information is included in the planning in MSF APS and is included in the production planning so that it remains within this determined date. If an operation is determined as a milestone in a project and if it is also shown in the plans when the completion information is received from the ERP, it is shown in the project step. Thus, the project milestones taken into the planning are automatically displayed on a chart.
The goals, outputs, or tasks that constitute the milestones of the projects are considered as moments in time fulfilled. These milestones created in MSF software must be in coordination with the calendar used in factory production and the scheduling created accordingly. When desired, the project milestone can trigger production, creating a production information milestone that starts in reverse. Or production start or end information can dynamically directly generate milestones of the prone. This allows projects to be viewed in a timeline, list or calendar view so that the interaction of milestones can be viewed in real-time in the most appropriate way.