Based on a sales forecast and customer orders, the production need of the sawmill is established.
Simulation software for cutting schemes and general business management software are used in combination for operational planning and production control.
The cutting scheme simulator is used to evaluate the different theoretical cutting parameters applicable to pine logs entering the industry. The optimal input of logs of each category and their best combination for the fulfillment of the plans is determined.
A simulation model is generated to estimate the values adopted by the variables when faced with different alternatives for the sawmill operation. Through the management control software, the sawmill operating variables are recorded, determining its production.
The results of the simulation process are compared with the real ones and the points on which measures for improvement should be applied are established.
Summary
Starting from a presage of sales and costumers orders, the necessity of production of the sawmill settles down.
A simulation software of logs split and a general software of administration are used in combined form for the operative planning and the production control.
The simulation of logs split is used to evaluate the different applicable theoretical parameters of the pins logs to process in the industry. The lumber products input is determined for the each category log and its best combination for the execution of the plans.
A simulation model is generated to estimate the variables values in different alternatives of the sawmill operation. By means of the software of administration control the variables of operation of the sawmill are registered, determining the sawmill production.
Introduction:
Decision making in sawing companies is not different from those that must be taken in any other type of company.
From the supply of logs from the forestations to the destination of the sawn material obtained, several processes take place.
Trees from afforestation can have different qualities depending on the age, the management to which the plantation was subjected, the origin of the material that was implanted, etc. Once the tree has been felled, it is cut into different dimensions depending on its diameter, its shape and the commercial lengths demanded by the boards to be obtained.
Based on the subsequent destination of the material resulting from sawing, the logs are classified and their processing is scheduled.
The plant manager is faced with a multitude of variables that range from the demand of his clients, the quality and volume of the logs to be processed, which, in turn, depend on the variables presented by the forestations that give rise to those logs..
To meet customer demand, the plant manager must select what type of logs should be purchased, deciding on the sawing scheme and applying a production schedule that meets customer requirements at a minimum cost.
Strategic planning is based on market expectations based on customer orders and sales forecasts, with the forecast of raw material supply at the other extreme.
Then we find the tactical planning that contemplates the production program determined by the infrastructure available to the company and that will allow it to achieve the forecast of future demand.
Operational planning encompasses the daily actions aimed at complying with the production schedule.
The plant manager must lead the actions aimed at achieving the strategic and tactical objectives established by the company's management.
He must program the quality and quantity of logs to be sawn, supplying the specification of the products to be obtained to the production manager, suggesting work times and the revisions that the program must undergo.
The critical point in this aspect of the plan are the cutting schemes that must be applied to the logs. The scheme applied to each category of logs depends on whether or not the expected production is achieved, both in quantity and in the degrees of specification of sawn wood. It is the responsibility of the production manager that the sawing line obtains the programmed results both in quantity and quality and in the planned work time.
In this work we present a model designed to facilitate the planning and control of sawmill operations. Emphasis is placed on tactical planning and operational planning.
This model includes a system that analyzes the cutting schemes to optimize the combination of logs, simulates the sawing process and a management control system to evaluate the results of the operation.
Materials and methods:
- For the analysis of the cutting schemes the Delta 96 software "Optimization of the Cutting Patterns" version 1.63 from Ciris Ingenierie (France) was used. For the optimization, the complementary Microsoft Excel tool called "Solver" was used. The simulation was generated with another Microsoft Excel add-in called "Crystal Ball" student version. As control software we use the Microsoft Access program given its applications for the optimization of company management control. (In each particular case, companies could adapt their specific management software). Probability distributions, both of the operating time of each cutting scheme and of performance (both resulting from analysis of the sawmill's real production), in our case were estimated as a normal distribution,considering the area below the mean, but in practical application they must arise from samplings carried out with statistical calculation techniques.
Results
Model structure:
The discussion presented above describes the necessary information about the key tasks and decisions that occur throughout the various phases of the sawing process.
Integrating all this information into a production schedule that includes all data inputs and outputs is a difficult but highly strategic task.
An inadequate production program will surely lead to high waste, a decrease in obtaining the expected products, inefficient allocation of available machine times, and all this will surely cause high economic losses. On the other hand, a careful allocation of resources through an efficient production program will enhance the economic results of the sawmill.
A plan of this type is almost impossible to apply if you do not have tools to obtain and process high-quality information.
This work describes a model whose purpose is to systematically analyze the sawing process. The primary objective of the model is to obtain a production program that encompasses optimum performance but which, in turn, is operationally applicable. This can be achieved by combining a cutting scheme analysis system with a management control system through a real-time production simulation model.
Operationally the model works as follows:
1. First, the best cutting schemes applicable to the different qualities of logs are determined using specific software.
2. This combination of logs is adjusted by evaluating the other available resources (machinery, labor, other inputs, etc).
3. Once the feasible cutting schemes have been established with the restrictions of the previous point, that information is transferred to a spreadsheet generating an optimization model that generates a production program.
4. This production program is simulated to determine the probable products to be obtained both in quantity and quality.
5. The results recorded in the management control program are contrasted with those of the simulation to determine the points for improvement.
Points 3 and 4 considered by us as the most important of this work are developed below.
Optimization of logs to be processed:
As discussed earlier, the plant manager is constantly faced with the problem of determining which combination of logs to process. The decision of the type of logs (diameters, lengths, etc.) to be sawn in a certain period depends on the demand for sawn products (qualities, thicknesses, widths, lengths) and the stocks available in the warehouses.
This is especially evident in those sawmills highly dependent on the demand situation.
The decision of logs to be processed confronts the plant manager with the business objective of maximizing economic efficiency, which can be expressed as follows:
Maximize G = Sum Pk * Qk-Sum Cy * Xy-Sum Py * Xy + SumMy * Wy
Where:
G = economic return
Pk = net price of quality sawn products k
Qk = quantity of quality sawn product k
Cy = Cost of sawing quality logs and
Xy = Volume of quality logs and
Py = Price of logs quality and
My = Volume of quality log by-products and
Wy = Net price of quality log by-products and
The variable that the plant manager can manage to meet both requirements (meet demand and maximize profit) is to minimize the cost of production formed by the operating cost of the sawmill and the cost of the logs processed.
This constitutes the "objective function" of the optimization model:
Min (Sum Cy * Xy + Sum Py * Xy), subject to the following restrictions:
1. Comply with customer orders and sales forecasts.
2. Stock available in warehouses
3. Total production must not exceed the probable maximum production of the sawmill (subject in turn to the maximum capacity of sawing and drying).
4. The theoretical yields of the preselected cutting schemes.
5. Cost of the different qualities of logs.
6. Operating cost of sawing and drying.
Simulation of the sawing and drying process:
Once the combination of logs to be processed and cutting schemes to be applied has been determined, the simulation of the sawing process is generated, whose “inputs” are:
1. the results of the optimization process
2. the theoretical yields of each cutting scheme
3. probability distribution of the yield of each cutting scheme (obtained from studies on actual sawmill production)
4. operating times of the sawmill for each cutting scheme
5. operating time probability distribution of each cutting scheme (resulting from analysis of the actual sawmill production)
The probability distribution curve of the products to be obtained is then obtained if the cut-off schemes established in the optimization process are applied.
Conclusion:
Advances in computer systems have spread to all types of industry, starting with high technology and then being adopted by other less technical industries, such as the sawmills that traditionally operate in the Province of Misiones.
They are currently facing highly competitive market conditions that in many cases put their continuity as a company at risk.
In this sense, this work demonstrates the feasibility of applying computer tools that are currently available to local industries, assisting management and allowing them to improve their profitability.
Thanks
To Establishment Maderero Chodorge SA that facilitated the use of the Delta 96 software "Optimization of Cutting Patterns" version 1.63.
Bibliography:
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CIRIS INGENIERIE. 1996. Delta 96 Version 1.63 User Manual. Ciris Ingenierie. Pessac. France.82pp.
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