Automating Raw Material Planning with MRP in Manufacturing Companies
Every manufacturing company eventually faces the same question: which raw materials should I purchase, when, and in what quantities? While the answer may seem straightforward, as order volumes increase, product variety expands, and supplier structures grow more complex, finding the right answer through manual methods becomes increasingly difficult. MRP (Material Requirements Planning) is a planning methodology developed to answer this question in a systematic and automated manner.
What Is MRP and How Does It Work?
MRP is a system that starts from the finished products in the production plan and calculates the raw material and semi-finished goods requirements listed in each product's bill of materials (BOM). By taking into account current stock levels, open purchase orders, and supplier lead times, it automatically determines which materials need to be ordered, when, and in what quantities.
The core inputs of MRP are: the master production schedule (which products will be manufactured, when, and in what quantities), bills of materials (which materials and how much of each are used to produce each product), current inventory levels and open orders, and supplier lead times and minimum order quantities. When these inputs are brought together, the MRP engine performs net requirements calculations and generates purchase suggestions.
MRP in Textiles and Apparel
The textile industry presents unique challenges for MRP implementation. Consider a shirt model: it requires dozens of different raw materials including fabric, buttons, thread, labels, and packaging. However, each size consumes a different amount of fabric, each color requires a different fabric lot, and product variety constantly changes due to seasonal collections.
An effective MRP system must be capable of managing this complexity. Reflecting size-based fabric consumption rates in the BOM, performing color-based raw material matching, and using collection-based production plans as MRP inputs are prerequisites for MRP to function correctly in the textile sector. For companies that outsource production through contract manufacturing, tracking raw materials sent to suppliers is also an integral part of this planning.
Recipe Management in Furniture Manufacturing
In the furniture industry, product recipes are typically multi-layered. Manufacturing a sofa requires foam, upholstery fabric, a wooden frame, metal mechanisms, bolts, screws, and packaging materials. However, some components are themselves semi-finished goods that require their own manufacturing processes: the wooden frame is crafted from raw lumber, and the foam is cut into specific molds.
In this multi-layered structure, MRP first identifies the requirements of the finished product and then calculates the raw materials needed to produce the semi-finished goods. In furniture companies that manufacture to order, each customer order may require a different fabric, color, or dimension combination, making it essential that recipes can be defined in a flexible and parametric manner.
Demand Forecasting and Production Planning
The quality of MRP outputs is directly proportional to the accuracy of its inputs. The most critical of these inputs is the master production schedule. For companies that manufacture to order, this plan is relatively clear-cut: existing orders translate directly into MRP inputs. However, companies that manufacture to stock must create their production plans through demand forecasting.
Historical sales data, seasonal trends, promotional calendars, and market analyses are among the key sources for demand forecasting. Sales data within the ERP system serves as the raw material for this analysis. A properly configured ERP reveals sales trends by category, channel, and region, thereby improving the reliability of demand forecasts.
Supplier Lead Times and Order Timing
One of MRP's most valuable outputs is determining when purchase orders need to be placed. This calculation is based on supplier lead times. If a fabric has a procurement lead time of 15 days and the production start date is September 1, MRP calculates that the order must be placed by August 17 at the latest.
Regularly monitoring supplier performance improves the accuracy of lead time estimates. When supplier parameters such as average delay durations, quality rejection rates, and minimum order quantities are defined in the ERP, MRP calculations produce more realistic results. The ability to define alternative suppliers is also an important component of supply risk management.
Automatic Purchase Order Suggestions
The purchase suggestions generated by MRP calculations are submitted for approval to the procurement department. These suggestions include the material code, required quantity, recommended supplier, order date, and requested delivery date. The procurement specialist reviews these suggestions, changes the supplier or adjusts quantities if necessary, and converts them into purchase orders upon approval.
This process becomes even more efficient with supplier-based order consolidation. Materials needed from the same supplier on different dates can be combined into a single order, reducing both shipping costs and making it easier to meet minimum order quantities.
Cost Optimization and Reporting
An MRP system does not merely determine when and how much to order; it also provides the foundation for accurate production cost calculations. When BOM data is combined with current raw material prices, the estimated production cost for each product can be calculated automatically. This information is used across numerous areas, from pricing decisions to preparing quotations.
Transitioning to MRP typically yields tangible results in manufacturing companies, including a 15 to 30 percent reduction in raw material inventory, increased inventory turnover rates, a noticeable decrease in supply delays, and a lighter operational burden on the procurement department. Achieving these results requires proper MRP configuration, complete BOM definitions, and keeping supplier parameters up to date.
