In this way, procurement documents are created at the planning stage which will eliminate all needs in the most ideal way. These documents can be easily converted to finalized documents with the module’s easy integration to the system. In addition, all supply documents opened for each demand document included in the supply chain are easily monitored and reported with the help of this module.
Each industry has its own variables in supply chain management and these variables can be significant for the planning strategy. caniasERP system ensures that the optimal planning method can be easily identified and implemented with the numerous parameters of the Material Requirements Planning module. In addition, the flexible structure of the module, allows simulations for possible scenarios using multiple planning strategies for a material.
Every organization would want to anticipate the future in order to take the necessary precautions against the changing market conditions. Based on this need, it is possible to make plans for future forecasts with the Material Requirements Planning module. It is very easy to determine the most appropriate estimation model by taking historical data into consideration, to make future sales data estimations using various estimation models, to make rough capacity planning on these predictions and to take necessary action in time for the organization.
The module provides different planning options for the same materials by using different setting types in order to plan with the conditions closest to reality. In this way, it is possible to observe the extent to which each possible scenario will affect the planning through simulation plans that can be carried out in parallel with the actual planning process of a material.
RICH TIME AND AMOUNT CALCULATION PARAMETERS
Material Requirements Planning module works fully deterministic. Requirement planning is done with perfect time accuracy so that the most suitable supply chain is created. In addition, the atomic time unit, if desired, can be determined by week, month, or a time period the user defines. This feature allows users to show tolerance and reduce the error rate in plan estimates. In addition, in the scheduling of the created plans, results that are closest to reality are acquired by using critical data such as order delivery time, production preparation/machinery/ labor times, purchase delivery time.
The module works perfectly in amount calculations. Many of the accepted industry standard order size determination methods are available in this module. In addition to linear methods such as Lot-for-lot, Fixed Quantity, Maximum Order Level, advanced methods such as Economic Order Quantity, Minimum Unit Cost, Minimum Total Cost and Part Period Balancing are used to determine order size. In addition, safety inventory and re-order point can be defined for the appropriate category of materials and minimum inventory management can be provided.
The Material Requirements Planning module allows the use of similar materials interchangeably. Thus, companies can consider a group of materials instead of a single material to meet their needs. This helps to reduce the extra purchase-production activities and promotes savings in enterprises. The choice between the materials defined as one other's alternatives on the system is made by taking the actual stock levels into account. Companies can manage the choice of the ideal alternative material according to the determined priority levels through the system.
The module provides different statistical forecasting models to plan the changes in needs in the future. For example, a demand estimate can be generated based on the sales figures of the relevant company. This estimation helps decision makers to better predict future developments and needs and to follow plans accordingly. In order to determine estimated demand amounts, advanced statistical methods such as linear regression analysis, seasonal indexing can be used as well as simple methods such as arithmetic mean. In addition, algorithms identifying and correcting errors in the data set that are the source of the demand forecast allow users to predict the future most closely in reality.
Material Requirements Planning module is fully integrated with the modules related to the materials, especially Base Data Management, Bill of Materials Management, Routing Management, Sales Management, Budget Management, Inventory Management, Production Management, Purchase Management and Transfer Management modules. Modules included in the integration provide instant data on all expected receipt and issue for planning. This keeps the system always up to date. Through the Net Exchange System, if any of the integration modules has a material change, the module automatically saves the information and re-plans the related material. With the help of collective planning applications, these materials and related materials are re-planned, and the plan status is updated to be a new current one. In addition, the system allows users to automatically run batch scheduling applications periodically.
Purchasing requests and production plans created by the Material Requirements Planning module are converted into real documents (purchase order and production order) through Production Management, Purchase Management and Transfer Management modules. Thus, the plans on the system are put into operation. In addition, this module monitors finalized documents and allows users to instantly view future stock status.
* Live material stock status
* Determination of definite and actual procurement dates
* Time parameters
* Lot size optimization methods
• Fixed quantity
• Maximum order level
• Economical order size
• Part period balanced
* Planning policies
Versatile planning configuration
Parallel planning and simulation
* Predict material movements between different facilities
* Keeping material plans up to date with net change system
* Planning for customer-based special order
* Use of alternative materials and material handling groups
* Realization of the created plans
* Rough Capacity Planning
* Matching of supply and demand documents
Updating of match records as the documents are realized
* Demand forecasting
Determining the appropriate demand estimation model
Prediction with multiple methods
Product and product family based demand forecast
Automatic detection and correction of missing or incorrect data
Ability to share forecast results with customers or vendors