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Overview : |
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| Planning and scheduling are common to many different engineering domains. Whether the project is a large one or something seemingly simple, both planning and scheduling are profoundly important. Even on a small project, the number of possible courses of action and the number of ways to allocate resources quickly becomes overwhelming. On a factory floor, determining which jobs should be executed on which machines by which employees can mean the difference between significant profit and debilitating loss. In a production shop floor, allocating the machines to the process activities, assigning responsibility to resources, effectively managing disruptions can mean the difference between a product that ships in time to hit a market window and a product that misses that window. Meeting number of constraints imposed by production process, Capacity constraints etc., and at the same time meeting the best production objectives can be a mammoth task. Furthermore the dynamic nature of the production requirements demands frequent changes in the schedules leading to complications. |
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From the time they are first defined, most plans and schedules are destined to change. Many job shop schedules change because of uncertainties in arrival times, quality rejections or due to unexpected equipment failures. Many project plans require modification when initial estimates are found to be inaccurate or when unexpected delays confound resource availabilities. Both planning and scheduling systems must be able to adapt to changes. A small change in the production plan or change of objective will require reworking with the whole plan, which is not only a tedious job but is also prone to human errors. With a change in plan the optimality achieved in the previous iteration may get lost. Manual planning could be a costly affair for manufacturing units.
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Apart from this, making a production plan manually based on above constraint needs highly trained and experienced personnel. Even large organizations do not have abundance of such people. It is more valuable for the organizations to utilize their time productively in decision making rather than fine-tuning plans. The dependence of organizations on the skills of the people responsible for production planning leaves a big void once they are not around. Optimization Engine for Automated Production Planning reduces the dependence on people and also saves their valuable time. |
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| Optimization Engine |
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Available techniques used for automated production planning and optimization like Tabu Search or Linear Programming are limited in scope and may not suffice for meeting multiple constraints. Most of the planning and scheduling problems cannot be easily represented by the existing linear techniques. Moreover, these techniques lead to exponentially increasing computation time with increase in number of constraints and process variables. Though the existing techniques may serve reasonably well to solve simpler problems with lesser constraints and variables, they may never converge to a viable solution when the production plan is complex. |
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| Optimization Engine for production scheduling gives factories the precision and speed, and provides the link between the high-level plans and the shop floor. The software accounts for varying production requirements, fixed limited number of Machines, BOM, Resource Availability, Downtime and sequencing constraints etc. With fixed limited number of machine and resources, and varying production requirements, it is important to optimize the usage of machines. Optimization Engine employs a range of well-known and proprietary algorithms to automatically generate the production plan and ensure optimality. For more complex problems where multiple constraints have to be optimized, the software employs techniques like Genetic Algorithm, which has the capability of generating near-optimal solutions in short period of time while accounting for large number of constraints. Genetic Algorithm involves generating a population of feasible solutions, measuring their fitness and selecting solutions for crossover or mutation to produce new solutions for the next population. This process will gradually transform the population and the solutions will converge to the near optimal. |
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| Benefits |
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| Optimization Engine can substantially reduce in the production cost in multiple ways. Firstly it reduces the level of inventory for all raw material and intermediate material required. Better capacity utilization obviates the need of maintaining a large inventory. The inventory replenishment module ensures no stocking of material in advance and helps in reduction of inventory. Secondly, better utilization of the capacity ensures maximum orders are met, resulting into higher returns. |
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| The overall benefits of the software will result in |
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Minimum Inventory Requirement |
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Optimal Utilization of Production Capacity |
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Optimal Utilization of Storage Capacity |
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Maximum Service Level |
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Order Prioritization leading to Maximized Profitability |
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Reduced time for Production Planning |
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Lesser Dependence on experience of the people |
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Easy handling of Multiple Constraints |
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Automatic Generation of Production Schedule |
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Faster convergence to a Solution |
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Reduced Production cost |
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| Solutions : |
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| a. |
Automatic Order Forecast: |
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Based on the previous Demand Data, software makes an Automatic Forecast for the orders to a high degree of accuracy. Forecast helps in accounting for the expected orders and reduces the risk due to fluctuating demand pattern. The demand forecast module is based on advanced modeling techniques, which can represent the highly dynamic and non-linear nature of the demand pattern. |
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| b. |
Optimized Production Plan: |
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The optimized production plan for meeting all the constraints defined is created. The optimized plan yields the best available solution for meeting the order requirements with the given constraints. Once the plan is created, it is accessible to the users for further manipulation as well. The production plan thus generated takes the following constraints into account and generates the start time for each activity. |
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Capacity Constraint |
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Human Resource Constraints |
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Product Sequencing Constraint |
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Downtime Constraints |
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Activity Continuity Constraint |
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Resource Availability Constraint |
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Minimum and Maximum Time Lags |
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Machine Usage Constraints |
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| The production plan thus generated is geared to meet the desired objectives of the plan optimally. |
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| c. |
Automatic Order Prioritization: |
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Order Prioritization is a decision support module, which determines the priorities of different orders based on the customer-ordering pattern and the order profitability. The user has the choice to override the priorities ascertained by the software based on the other constraints. Automatic Order Prioritization takes the overall organization objective into account. |
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| d. |
Inventory Replenishment Plan: |
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To ensure minimum inventory level, the material stocking cannot be done at the beginning of the production process. At the same time, the replenishment cannot be carried out in true real-time, as the shipment cost will be high. Depending upon the Current Inventory levels, Supplier order lead-time, Demand characteristics, Customer service levels etc., the software suggests, how much to buy and which supplier to buy from. The replenishment pattern could be as shown below. |
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| e. |
Resource Allocation: |
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The software maintains a central database for human resource availability at all times. Based on the skill set requirements of the activities and the availability of the resources, it finds out the best-fit resources for carrying out the tasks and allocates the resources to the activities. It ensures that no resource is overloaded with work and each resource's leaves and other non-working times are taken care of. |
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| f. |
Human Resource Supply-Demand: |
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| Based on the allocation of the resources to the tasks, the software generates overall resource allocation status. This helps the resource managers plan the resource recruitment, resource movement across different divisions efficiently. |
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| g. |
Customer Service Level: |
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From the production plan generated, the software suggests the service level offered to different customers. It suggests the delay in delivery dates of the orders, if any.
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| System Architecture |
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| The core optimization engine of the software is written on C/C++, which is compliant to multiple platforms including Windows 3.x/95/98/2000/NT, Unix and Linux. The software provides easy to use interfaces for the users to enter the necessary input data. The users can define their process details bill of material and other details as described above on user-friendly interfaces. The interfaces allow the users to carry out almost entire production planning manually as well. The optimization engine generates the entire schedule and makes it accessible to the user on these interfaces for further manipulation. The software also integrates with leading planning applications like MS-Project etc. Apart from that, the Software can be integrated with the existing ERP systems in the organization. The software provides high speed scheduling with numerous configurable constraints, a rich GUI, and no limit on data size. |
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| The software also integrates with leading planning applications like MS Excel, MS-Project etc. Apart from that, the Software can be integrated with the existing ERP systems in the organization. |
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The software provides high speed scheduling with numerous configurable constraints, a rich GUI, and no limit on data size. |
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