Solving a Real Problem in Plastic Industry: A Case in Trim-loss Problem (original) (raw)
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Solving real problem in plastic industry: A case in trim-loss problems
2018
In this paper we present a cutting plane model for solving a problem in a cast polypropylene (CPP) plastic film manufacturer. The company produces plastic rolls from plastic pellets with widths ranging from 3050 mm to 3250 mm. The plastic rolls are trimmed according to customer�s orders. Before this work has been done, the PPIC department�s scheduled the machines and arranged the plastic trim compositions manually. In this work we solve the plastic trimming problem by applying the trim loss model. We used the visual basic for application (VBA) based program to Excel. We then use the model outcomes for optimizing the machine scheduling process. We proposed modified earliest due date for scheduling the machine that represents the realities in the company
An effective solution for a real cutting stock problem in manufacturing plastic rolls
Annals of Operations Research, 2009
We confront a practical cutting stock problem from a production plant of plastic rolls. The problem is a variant of the well-known one dimensional cutting stock, with particular constraints and optimization criteria defined by the experts of the company. We start by giving a problem formulation in which optimization criteria have been considered in linear hierarchy according to expert preferences, and then propose a heuristic solution based on a GRASP algorithm. The generation phase of this algorithm solves a simplified version which is rather similar to the conventional one dimensional cutting stock. To do that, we propose a Sequential Heuristic Randomized Procedure (SHRP). Then in the repairing phase, the solution of the simplified problem is transformed into a solution to the real problem. For experimental study we have chosen a set of problem instances of com-mon use to compare SHRP with another recent approach. Also, we show by means of examples, how our approach works over instances taken from the real production process.
Scheduling Cutting Process for Large Paper Rolls
Academic Platform Journal of Engineering and Science, 2013
Paper cutting is a simple process of slicing large rolls of paper, jumbo-reels, into various sub-rolls with variable widths based on demands risen by customers. Since the variability is high due to collected various orders into a pool, the process turns to be production scheduling problem, which requires optimisation so as to minimise the final remaining amount of paper wasted. The problem holds characteristics similar one-dimensional bin-packing problem to some extends and differs with some respects. This paper introduces a modelling attempt as a scheduling problem with an integer programming approach for optimisation purposes. Then, a constructive heuristic algorithm revising one of well-known approaches, called Best-fit algorithm, is introduced to solve the problem. The illustrative examples provided shows the near optimum solution provided with very low complexity.
A Mathematical Model for Reduction of Trim Loss in Cutting Reels at a Make-to-Order Paper Mill
Applied Sciences, 2020
One of the main issues in a paper mill is the minimization of trim loss when cutting master reels and stocked reels into reels of smaller required widths. The losses produced in trimming at a paper mill are reprocessed by using different chemicals which contributes to significant discharge of effluent to surface water and causes environmental damage. This paper presents a real-world industrial problem of production planning and cutting optimization of reels at a paper mill and differs from other cutting stock problems by considering production and cutting of master reels of flexible widths and cutting already stocked over-produced and useable leftover reels of smaller widths. The cutting process of reels is performed with a limited number of cutting knives at the winder. The problem is formulated as a linear programming model where the generation of all feasible cutting patterns determines the columns of the constraint matrix. The model is solved optimally using simplex algorithm wi...
2007
In this paper the cutting stock problem for the corrugated board boxes industry is presented. The problem is solved by means of a two step strategy. First, patterns pre-generation model is formulated which are then used as input in a mathematical MILP model that optimizes the cutting process minimizing the paper trim-loss costs. Several parameters have been added to the system such that the planner can manipulate its values to produce a solution according to their customer demands. The system has been linked to the company ERP and is now in production.
The combined cutting stock and lot-sizing problem in industrial processes
European Journal of Operational Research, 2006
Despite its great applicability in several industries, the combined cutting stock and lot-sizing problem has not been sufficiently studied because of its great complexity. This paper analyses the trade-off that arises when we solve the cutting stock problem by taking into account the production planning for various periods. An optimal solution for the combined problem probably contains non-optimal solutions for the cutting stock and lot-sizing problems considered separately. The goal here is to minimize the trim loss, the storage and setup costs. With a view to this, we formulate a mathematical model of the combined cutting stock and lot-sizing problem and propose a solution method based on an analogy with the network shortest path problem. Some computational results comparing the combined problem solutions with those obtained by the method generally used in industry-first solve the lot-sizing problem and then solve the cutting stock problem-are presented. These results demonstrate that by combining the problems it is possible to obtain benefits of up to 28% profit. Finally, for small instances we analyze the quality of the solutions obtained by the network shortest path approach compared to the optimal solutions obtained by the commercial package AMPL.
A New Decision Model for Reducing Trim Loss and Inventory in the Paper Industry
Journal of Applied Mathematics, 2014
In the paper industry, numerous studies have explored means of optimizing order allocation and cutting trim loss. However, enterprises may not adopt the resulting solutions because some widths of the inventory exceed or are less than those required for acceptable scheduling. To ensure that the results better suit the actual requirements, we present a new decision model based on the adjustment of scheduling and limitation of inventory quantity to differentiate trim loss and inventory distribution data. Differential analysis is used to reduce data filtering and the information is valuable for decision making. A numerical example is presented to illustrate the applicability of the proposed method. The results show that our proposed method outperforms the manual method regarding scheduling quantity and trim loss.
Mathematical Problems in Engineering, 2014
We consider a one-dimensional cutting stock problem (CSP) in which the stock widths are not used to fulfill the order but kept for use in the future for the industrial-use paper production. We present a new model based on the flexible stock allocation and trim loss control to determine the production quantity. We evaluate our approach using a real data and show that we are able to solve industrial-size problems, while also addressing common cutting considerations such as aggregation of orders, multiple stock widths, and cutting different patterns on the same machine. In addition, we compare our model with others, including trim loss minimization problem (TLMP) and cutting stock problem (CSP). The results show that the proposed model outperforms the other two models regarding total flexibility and trim loss ratio.
1995
This paper investigates properties of integer programming models for a class of productionplanning problems. The models are developed within a decision support system to advise a sales teamof the products on which to focus their efforts in gaining new orders in the short term. The productsgenerally require processing on several manufacturing cells and involve precedence relationships. Thecells are already (partially) committed with products for stock and to satisfy existing orders and...