Search

We propose a batch-scheduling model to minimize the total actual flow time (TAF) of parts to be processed in a flow shop consisting of m batch-processing machines. A batch-processing machine (BPM) is a machine that can process several parts at once, and the TAF of parts is the total interval time from the arrival times to the corresponding due date. In the real world, shop floors often have production lines with BPMs and multistage processes. We were motivated by a real problem in the aircraft industry and aimed to simultaneously satisfy the due dates and minimize the total time that parts spend in the shop. The problem was formulated as a mathematical model and solved using a proposed algorithm. The batch-scheduling problem is divided into batching and scheduling subproblems. The solution has been obtained by adopting backward scheduling. This paper develops a new model of flow shop scheduling problem for the shop with batch processing machines and the heuristic solution method. It provides numerical examples and their results to demonstrate the effectiveness of the proposed algorithm for solving the problem.

We propose a batch-scheduling model to minimize the total actual flow time (TAF) of parts to be processed in a flow shop consisting of m batch-processing machines. A batch-processing machine (BPM) is a machine that can process several parts at once, and the TAF of parts is the total interval time from the arrival times to the corresponding due date. In the real world, shop floors often have production lines with BPMs and multistage processes. We were motivated by a real problem in the aircraft industry and aimed to simultaneously satisfy the due dates and minimize the total time that parts spend in the shop. The problem was formulated as a mathematical model and solved using a proposed algorithm. The batch-scheduling problem is divided into batching and scheduling subproblems. The solution has been obtained by adopting backward scheduling. This paper develops a new model of flow shop scheduling problem for the shop with batch processing machines and the heuristic solution method. It provides numerical examples and their results to demonstrate the effectiveness of the proposed algorithm for solving the problem. [ABSTRACT FROM AUTHOR]

This paper addresses a batch scheduling problem for a three-stage hybrid flowshop consisting of a machining stage processing common and unique components on unrelated parallel machines, an assembly stage combining the components into assembled products with complex assembly structures, and a differentiation stage processing the assembled products on dedicated machines to produce different product types. The common components are the same for all products and are processed in batches, while the unique components are dedicated to respective given product types and are processed individually (one-by-one component). The goal is to schedule all the products with different assembly structures to minimize total actual flow time (TAFT) defined as total time interval of components to be processed from their arrival times to their common due date. A non-linear programming model is proposed, where small size problems can be solved optimally using the LINGO software, and large size problems is to be solved using a heuristic algorithm. The proposed algorithm consists of two sub-algorithms. The first one is constructed using a shortest processing time (SPT) based heuristic to get a job sequence as an initial solution and the second one is to improve the initial solution using the variable neighbourhood descent (VND) method with neighbourhood insert and swap move operators. In solving the problem with the algorithm, two scenarios arise, e.g., the same and the different sequences for all stages. A set of hypothetical data is generated for different hierarchical assembly structures to test the model and the algorithm, and the results show that the different sequences for all stages obtain solutions with better performances than the same ones.

This paper addresses a batch scheduling problem for a three-stage hybrid flowshop consisting of a machining stage processing common and unique components on unrelated parallel machines, an assembly stage combining the components into assembled products with complex assembly structures, and a differentiation stage processing the assembled products on dedicated machines to produce different product types. The common components are the same for all products and are processed in batches, while the unique components are dedicated to respective given product types and are processed individually (one-by-one component). The goal is to schedule all the products with different assembly structures to minimize total actual flow time (TAFT) defined as total time interval of components to be processed from their arrival times to their common due date. A non-linear programming model is proposed, where small size problems can be solved optimally using the LINGO software, and large size problems is to be solved using a heuristic algorithm. The proposed algorithm consists of two sub-algorithms. The first one is constructed using a shortest processing time (SPT) based heuristic to get a job sequence as an initial solution and the second one is to improve the initial solution using the variable neighbourhood descent (VND) method with neighbourhood insert and swap move operators. In solving the problem with the algorithm, two scenarios arise, e.g., the same and the different sequences for all stages. A set of hypothetical data is generated for different hierarchical assembly structures to test the model and the algorithm, and the results show that the different sequences for all stages obtain solutions with better performances than the same ones. [ABSTRACT FROM AUTHOR]

Most classical scheduling approaches deal with single products, single machines, and static manufacturing environments. In real-world manufacturing systems, however, scheduling can be assigned for multi-item production on multimachines in a dynamic environment in which unexpected new orders may be received. This paper focuses on scheduling problems in an assembly job shop with parallel machines that produce multi-item multi-level products. Models were developed for due date fulfillment and due date assignment in static and dynamic conditions, with the objectives of minimizing total actual flow time, while considering the defect rate at each stage of the process. The insertion technique was used in the scheduling process; insertion can be performed in batch operations at all available positions on all machines. A hypothetical case of job shop scheduling problems associated with multi-item, multi-level production on parallel machines was studied, and the computational results demonstrated the validity of the proposed algorithms. [ABSTRACT FROM AUTHOR]