Manufacturing
Since the 1960s, manufacturers have relied on material requirements planning (MRP) calculations to plan and manage optimal inventory of dependent demand materials. Both a methodology and a software system, MRP was revolutionary in its ability to accurately determine inventory needs and help companies meet the demands of an evolving consumer marketplace. While its underlying principals – including its core calculation – are still relevant and commonly practiced today, MRP is now typically part of a broader software ecosystem, used in conjunction with manufacturing execution systems (MES), manufacturing resource planning (MRP II), enterprise resource planning (ERP), distribution resource planning (DRP) and production planning systems.
The success of any manufacturing company is determined by its ability to manage inventory to meet demand. MRP is a planning and control tool that uses bill of material (BOM) data, inventory records and the master production schedule to calculate the amount of dependent demand items such as raw materials, components and subassemblies needed to produce a finished good according to its demand-driven production schedule.
MRP answers the following three essential manufacturing questions:
- What do I need?
- How much do I need?
- When do I need it?
The objective of MRP is to keep as little on-hand inventory as possible to minimize carrying costs and waste, but enough to satisfy current and future demand and fulfill planned orders. While the MRP calculation can be carried out by hand, it is most commonly performed electronically, either by a homegrown, hybrid or dedicated MRP software solution.
Developed by engineer Joseph Orlicky and others in the 1950s and 1960s, MRP was born of a need for greater control, accuracy and efficiency of core manufacturing processes such as inventory and production management. Prior to the advent and accessibility of computing technology, these activities were reactive and typically relied on historical demand as opposed to current and future needs, which proved to be an inefficient approach in a rapidly changing and globalizing manufacturing landscape.
As a result, MRP was among the first enterprise software systems to be widely adopted in the 1970s. MRP was the precursor to manufacturing resource planning (MRP II) developed in the 1980s, and later enterprise resource planning (ERP) which has been widely used since the 1990s.
By calculating the optimal balance between inventory and demand, MRP gives companies a competitive advantage by allowing them to increase productivity and efficiency, thus reducing overall manufacturing costs. But the effectiveness of MRP is also affected by several limitations:
Data integrity – Since MRP relies on input data, the accuracy of that data is critical to the accuracy of MRP output data. If there are errors in the inventory records, BOM data or master production schedule, the MRP calculations cannot be relied upon.
Sales variance –MRP is highly useful for planning future inventory and production needs based on demand forecasts, but is vulnerable to variance in actual sales.
Blind spots – MRP fails to account for constraints in staffing, machine or supplier capacity. It also does not consider the physical location of facilities or inventory stock, nor the potential benefits (e.g., price discounts) of ordering a material in bulk versus for each individual job.
MasterControl Manufacturing Excellence solutions optimize MRP programs by automating manual processes and fully integrating with existing enterprise software systems to support companies on their smart manufacturing and digital transformation journeys. MasterControl Manufacturing Excellence software can help manufacturers:
Digitize, integrate and automate your manufacturing processes to improve efficiency and accuracy.
Automatically generate consistent, compliant and customized manufacturing documentation including device history records (DHR), production travelers, history records, batch records, batch production records (BPR) and more.
Improved visibility and predictive analytics allow for process improvements to be made in real time.
Gain performance insights to improve the efficiency of both your machines and your people.
Delays, bottlenecks and quality events can be easily identified to resume production as quickly as possible.
Replace manual, paper-based documentation processes with a more streamlined and automated approach.