Introduction

Customer service plays a central role in achieving marketing objectives for firms in the consumer goods industry. The most important element of customer service is product availability. Commonly measured as the fill rate for incoming orders, product availability depends on the amount of end-item inventory in situations where a make-to-stock policy exists. Manufacturing firms in the consumer goods industry adopt the make-to-stock policy because the manufacturing lead-time for end-items is often longer than the cycle time for taking and shipping an order.

The main tool to control product availability is the master production schedule (MPS). By using the beginning inventory and the sales forecast for a particular end item, a planner can calculate the amount of production needed per period to meet anticipated customer demand. This calculation becomes more complex in a multi-product environment where forecast errors and capacity constraints can add a great deal of uncertainty to the planning process. As firms continue to integrate the MPS into logistical planning, it is becoming increasingly clear that MPS stability plays a major role in managing the trade-off between costs and product availability.

MASTER PRODUCTION SCHEDULE

A Master Production Schedule (MPS) is a plan for production, staffing, inventory, etc. It is usually linked to manufacturing where the plan indicates when and how much of each product will be demanded. This plan quantifies significant processes, parts, and other resources in order to optimize production, to identify bottlenecks, and to anticipate needs and completed goods. Since an MPS drives much factory activity, its accuracy and viability dramatically affect profitability. Typical MPS's are created by software with user tweaking.

Due to software limitations, but especially the intense work required by the "master production schedulers", schedules do not include every aspect of production, but only key elements that have proven their control affectivity, such as forecast demand, production costs, inventory costs, lead time, working hours, capacity, inventory levels, available storage, and parts supply. The choice of what to model varies among companies and factories. The MPS is a statement of what the company expects to produce and purchase (ie. quantity to be produced, staffing levels, dates, available to promise, projected balance).

The MPS translates the business plan, including forecast demand, into a production plan using planned orders in a true multi-level optional component scheduling environment. Using MPS helps avoid shortages, costly expediting, last minute scheduling, and inefficient allocation of resources. Working with MPS allows businesses to consolidate planned parts, produce master schedules and forecasts for any level of the Bill of Material (BOM) for any type of part.

The Master Production Scheduling (MPS) function has grown from an MRP-driver to a management function which coordinates Production and Sales and translates the company's long term plans into detailed production decisions to control the good show. Therefore each company, though often implicitly, has an MPS function. The existing frameworks in literature however are not always valid to model the MPS function in different types of companies.

A Master Production Schedule or MPS is the plan that a company has developed for production, inventory, staffing, etc.  It sets the quantity of each end item to be completed in each week of a short-range planning horizon. A Master Production Schedule is the

master of all schedules.  It is a plan for future production of end items.

MPS INPUTS: Forecast DemandProduction CostsInventory CostsCustomer OrdersInventory LevelsSupplyLot SizeProduction Lead TimeCapacity

MPS OUTPUT (production plan):

Amounts to be ProducedStaffing LevelsQuantity Available to PromiseProjected Available Balance

Features of master production schedule

Accepts and consolidates independent demand from Manual Forecasts, Sales Forecasts, Customer Orders and Electronic (EDI) Customer Releases.

Allows extensive manipulation of draft master schedules through menu features such as rolling, netting, scrap factoring, and lot sizing.

Provides Net Change analysis between two master production schedules.

Prints the Master Production Schedule in 12 day, 4 week, 12 week and 12 month formats.

Provides rough-cut capacity planning to evaluate feasibility of the Master Production Schedule in terms of critical materials, manpower, machines and finances.

Provides Sales Forecasting for one and five year horizons.

Forecasts demand using moving average, weighted moving average, and exponential smoothing with seasonal and economic trend adjustments.

Prints Sales Forecasts in units or dollars.

Generates a Master Production Schedule (MPS) file for use by the MRP application.

Maintains multiple shop calendars.

Provides long horizons for capacity and resource planning.

How MASTER PRODUCTION SCHEDULE works

By using several variables as inputs the MPS will generate a set of outputs used for decision making. Inputs may include forecast demand, production cost, inventory costs, customer orders, inventory levels, supply, lot size, production lead time, and capacity. Inputs may be automatically generated by an ERP system that links a sales department with a production department. For instance, when the sales department records a sale, the forecast demand may be automatically shifted to meet the new demand. Inputs may also be inputted manually from forecasts that have also been calculated manually. Outputs may include amounts to be produced, staffing levels, quantity available to promise, and projected available balance. Outputs may be used to create a Material Requirement Planning (MRP) schedule.

A master production schedule may be necessary for organizations to synchronize their operations and become more efficient. An effective MPS ultimately will:

Give production, planning, purchasing, and management the information to plan and control manufacturing

Tie overall business planning and forecasting to detail operations

Enable marketing to make legitimate delivery commitments to warehouses and customers

Increase the efficiency and accuracy of a company's manufacturing.

Example of master production schedule:

MASTER PRODUCTION SCHEDULE IN SALES AND PRODUCTION

The MPS serves the following functions:

1.POWERFUL SCHEDULING TOOL

Master scheduling requires ongoing analysis,measurement and adjustment to achieve revenue goalsand ensure profitability through the careful allocation ofmaterials and resources. MPS gives you a set ofpowerful tools for resource planning and scheduling,analysis, and performance measurement.

2.PLANNER’S WORKBENCH

A Planner’s Workbench provides the means forconsolidating all planning and scheduling functions ontoone easy-to-use screen. The workbench gives youimmediate access to information in all areas necessaryfor successful planning / scheduling including salesdemand, committed production, and purchased andplanned supply. This allows planners, analysts, andprogram managers to react quickly and easily to anyexceptions that occur.

3.COMPLETE PLANNING VISIBILITY

To help resolve any conflicts, MPS takes a variety ofvariables into account, including available inventory,forecasted sales, actual backlog, and firm plannedproduction, among others.

4.“WHAT IF” SIMULATION

A “What If” simulation capability ensures the bestpossible manufacturing scenario by allowing you toanalyze the effects of alternate scenarios, using eithercurrent or simulated data.

5.SCHEDULING CYCLES

And because no single view of your supply and demanddata can satisfy all of your planning needs, MPSenables you to create and maintain an unlimited numberof planning scenarios. One for near-term deliveries, another for long-range production capacities, and so on.Each cycle provides a unique view of the informationNecessary to help you develop the correct priorities foryour factory.

6.PERFORMANCE MEASUREMENT

MPS can give you an on-line “snapshot” estimation ofthe profit or loss that your build plan will yield.Performance analysis can be based on current orsimulated data. This helps you focus on areas ofmaximum payback and set priorities before committingcritical resources.