PRODUCTION SCHEDULING IN THE PROCESS INDUSTRY (original) (raw)
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A case study of production scheduling in a chemical industry
Engineering Costs and Production Economics, 1989
The problem concerns the production of "woodstock"p1ate.s in a workshop ofa chemical industry; several, but not identical, machines may be used to process a set of jobs. A job is characterized by various parameters so that the efficiencies of the machines are different for a specific job. Change-over times exist to adopt a machine between two successive jobs. The main objective is to assign and schedule the jobs to minimize the makespan, but some due dates must eventually be taken into account.
Industrial & Engineering Chemistry Research, 2002
The medium-range production scheduling problem of a multi-product batch plant is studied. The methodology consists of a decomposition of the whole scheduling period to successive short horizons. A mathematical model is proposed to determine each short horizon and the products to be included. Then a novel continuous-time formulation for short-term scheduling of batch processes with multiple intermediate due dates is applied to each time horizon selected, leading to a large-scale mixed-integer linear programming (MILP) problem. Special structures of the problem are further exploited to improve the computational performance. An integrated graphical user interface implementing the proposed optimization framework is presented. The effectiveness of the proposed approach is illustrated with a large-scale industrial case study that features the production of thirty five different products according to a basic 3-stage recipe and its variations by sharing ten pieces of equipment. ¢ 7 ¢ 8 ¢ 9 ¢ 1 0 ¢ 1 1 ¢ 1 2 . However, it should be pointed out that all slot-based formulations 6 ¢ 7 ¢ 8 restrict the time representation and result by definition in suboptimal solutions. Floudas and coworkers 13 ¢ 1 4 ¢ 1 5 proposed a novel true continuous-time mathematical model for the general short-term scheduling problem of batch, continuous and semicontinuous processes, which is the basis of the work presented in this paper. Lin and Floudas 16 further extended this model to incorporate scheduling issues in the design and synthesis of multipurpose batch processes.
In this work, we describe a framework for short-term and medium-term scheduling of a large-scale industrial continuous plant. For medium-term scheduling, two sub-problems are solved using a rolling-horizon based decomposition scheme. An upper-level model is used to find the optimal number of products, and the length of the time horizon to be considered for solving the lower level short-term scheduling problem. At the lower level, we proposed an improved model for short-term scheduling of continuous processes using unit-specific event-based continuous-time representation. The proposed formulation is demonstrated on a large-scale industrial case study comprising up to 100 units with 1/3 processing and 2/3 storage units operating in a continuous-mode for producing more than 100 different products over a one month time horizon.
A Mathematical Model for Production Planning and Scheduling in a Production System: A Case Study
2019
Integration in decision making at different organizational and time levels has important implications for increasing the profitability of organizations. Among the important issues of medium-term decision-making in factories, are production planning problems that seek to determine the quantities of products produced in the medium term and the allocation of corporate resources. Furthermore, at short-term, jobs scheduling and timely delivery of orders is one of the vital decision-making issues in each workshop. In this paper, the production planning and scheduling problem in a factory in the north of Iran is considered as a case study. The factory produces cans and bins in different types with ten production lines. Therefore, a mixed integer linear programming (MILP) model is presented for the integrated production planning and scheduling problem to maximize profit. The proposed model is implemented in the GAMS software with the collected data from the real environment, and the optimal...
Scheduling of a multi-product batch process in the chemical industry
Computers in Industry, 1998
We present an example of a mixed-integer linear programming (MILP) model for the scheduling of a multi-product batch process occurring in the chemical industry. The batch process considered is organized in several stages. Various final products are produced out of a single feedstock by a number of chemical processes. The major scheduling objective is to minimize the makespan, i.e. to complete the required production operations within the shortest possible time. The complexity of the scheduling problem is determined by such factors as variable batch sizes, shared intermediates, flexible proportions of output goods, blending processes, sequence and usage dependent cleaning operations, finite intermediate storage, cyclical material flows, and no-wait production for certain types of products. Due to the fact that computational times are prohibitive for problems of realistic size, we develop various LP-based heuristics. The heuristics proposed are applied to relaxations of the original multi-period MILP model. Thus, computational results are obtained a magnitude faster. Furthermore, near-optimal solutions are made possible for larger problems within reasonable computational time. In order to evaluate the applicability of the heuristics a number of numerical experiments were performed.
E3S Web of Conferences
Production is one of the most important activities which guarantee the continued existence of man; however, it comes with its challenges which make it very difficult to meet up the consumer’s demand. In this regard, the system is required by production and manufacturing companies, human resources, and materials to be enhanced by scheduling and planning of production. In addressing this problem of scheduling over a mid-term possibility, material flow and production objectives should be forecast by solving the problems of planning. Only when the production planning problems have been solved then scheduling problems could be addressed. In this work, we relate scheduling with capacity planning in relation to the production of goods and services. Also reviewed the common problems associated with the industry and how they are overcome.
A continuous time model for a short-term multiproduct batch process scheduling
In the chemical industry, it is common to find production systems characterized by having a single stage or a previously identified bottleneck stage, with multiple non-identical parallel stations and with setup costs that depend on the production sequence. This paper proposes a mixed integer production-scheduling model that identifies lot size and product sequence that maximize profit. It considers multiple typical industry conditions, such as penalties for noncompliance or out of service periods of the productive units (or stations) for preventive maintenance activities. The model was validated with real data from an oil chemical company. Aiming to analyze its performance, we applied the model to 155 instances of production, which were obtained using Monte Carlo technique on the historical production data of the same company. We obtained an average 12 % reduction in the total cost of production and a 19 % increase in the estimated profit.
Processes
Scheduling is a major component for the efficient operation of the process industries. Especially in the current competitive globalized market, scheduling is of vital importance to most industries, since profit margins are miniscule. Prof. Sargent was one of the first to acknowledge this. His breakthrough contributions paved the way to other researchers to develop optimization-based methods that can address a plethora of process scheduling problems. Despite the plethora of works published by the scientific community, the practical implementation of optimization-based scheduling in industrial real-life applications is limited. In most industries, the optimization of production scheduling is seen as an extremely complex task and most schedulers prefer the use of a simulation-based software or manual decision, which result to suboptimal solutions. This work presents a comprehensive review of the theoretical concepts that emerged in the last 30 years. Moreover, an overview of the contri...
Optimization of production scheduling in a PET chemical processing plant
In this paper, we present a mixed integer linear program for production scheduling in a PET (polyethylene terephthalate) bottle production plant that produces four different types of final product (resins). The production of the PET containers is a tedious task whose scheduling requires careful design, due to the existence of a large number of parameters that increase the complexity of the problem. Due to the fact that low quality intermediate products with nonstandardized characteristics are produced when switching from one type of resin to another, the model focuses on minimizing the quantities of these products (therefore, the associated costs, too), while also ensuring that the capacity constraints of the facility are not violated and that the demand for final products is satisfied on time. We present a case study that illustrates the application of the model on a real world scenario and provides insight into its behavior. The results are very encouraging, because they demonstrate that the model performs quite successfully, even for large problem instances. We conclude this work with a discussion of the applicability and the flexibility of the model based on the analysis of the results obtained.
Production scheduling for continuous manufacturing systems with quality constraints
This research is motivated by a real world production scheduling problem in a continuous manufacturing system involving multiple objectives, multiple products and multiple processing lines with various inventory, production and quality constraints. Because of the conflicting objectives, a global optimization approach is considered as not feasible by the plant management. Given a customer demand forecast, two practical heuristic or sequential optimization algorithms are developed to generate daily production schedules for two primary objectives: minimize shipment delays (pull-backward procedure) and minimize average inventory levels (push-forward procedure). A third heuristic algorithm (reduce switch-over procedure) which is based on the current management practice is also developed to serve as a benchmark. A factorial experiment was performed to evaluate the performance of the heuristic procedures and to identify factors that might affect the performance differences among heuristics. Since each heuristic is designed to give priority to one of the three conflicting objectives, none of them is absolutely superior to the other algorithms in all aspects. However, the first two heuristic procedures performed better than the current management practice in shipment delays and average daily inventory. The production schedules generated by the two procedures also satisfy the quality constraints. The experimental results also showed that the performance of the algorithms is significantly affected by product mix, inventory levels, and demand pattern.