A lexicographic approach to bi-objective scheduling of single-period orders in make-to-order manufacturing

Alazzam²,

IEEE Trans. Compon., Packag. Manufact. Technol.

et al. 2015

In this paper, a stochastic model is developed to analyze the performance of a flexible manufacturing cell (FMC). The FMC considered in this paper consists of a single conveyor, a single robot, and one or more machine(s). The conveyor belt delivers the working part to the robot, which loads it onto the machine. A Markov chain model is constructed for one-machine and twomachine FMCs, after which the model is generalized to an FMC with n machines. Most importantly, the model provides an estimate of the overall machine utilization and production rate for the FMC under consideration and also illustrates the effect of different operational factors on machine utilization and production rate. The results indicated that the overall machine utilization increases with conveyor belt and robot delivery rates and decreases with machine rate, as expected. However, this decrease or the increase in the overall machine utilization is sharp at low levels of each parameter (e.g., conveyor belt delivery and robot loading), but it gradually stabilizes at higher levels of the parameters. Finally, the production rate increases sharply at low levels of each parameter and gradually stabilizes at higher levels.Index Terms-Flexible manufacturing cell (FMC), Markov chain, multiple machine, single machine.

Section: Proposed Modelmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 98%

Multimachine Flexible Manufacturing Cell Analysis Using a Markov Chain-Based Approach

Alazzam²,

IEEE Trans. Compon., Packag. Manufact. Technol.

et al. 2015

International Journal of Production Research

“…, m stages during the same planning period. As a result, the available capacity c it is smaller than simply the available machine hours in period t; c it can be bounded as follows (Sawik 2007a):…”

Section: Problem Descriptionmentioning

confidence: 99%

Multi-objective due-date setting in a make-to-order environment

Sawik

2009

Self Cite

This paper presents a new dual-objective problem of due-date setting over a rolling planning horizon in make-to-order manufacturing and proposes a bi-criterion integer programming formulation for its solution. In the proposed model the due-date setting decisions are directly linked with available capacity. A simple critical load index is introduced to quickly identify the system bottleneck and the overloaded periods. The problem objective is to select a maximal subset of orders that can be completed by the customer requested dates and to quote delayed due dates for the remaining acceptable orders to minimise the number of delayed orders or the total number of delayed products as a primary optimality criterion and to minimise total or maximum delay of orders as a secondary criterion. A weighted-sum program based on a scalarisation approach is compared with a two-level due-date setting formulation based on the lexicographic approach. In addition, a mixed-integer programming model is provided for scheduling customer orders over a rolling planning horizon to minimise the maximum inventory level. Numerical examples modeled after a realworld make-to-order flexible flowshop environment in the electronics industry are provided and, for comparison, the single-objective solutions that maximise total revenue subject to service level constraints are reported.

“…One of the basic goals of aggregate production planning is to maximize the customer service level; that is, to maximize the fraction of customer orders fulfilled on time. A typical customer due-date-related performance measure is the minimization of the number of delayed orders; e.g., Sawik (2007). Simultaneously, increasing competition forces manufacturers to achieve low unit costs by highly and evenly utilizing its renewable production resources (e.g., machines and people) and by minimizing the inventory.…”

Section: Aggregate Production Planningmentioning

confidence: 99%

Mixed Integer Programming Approaches to Planning and Scheduling in Electronics Supply Chains

Sawik

2017

dmms

Self Cite

Abstract. This paper discusses mixed-integer programming (MIP) approaches to planning and scheduling in electronics supply chains. First, the short-term detailed scheduling of wafer fabrication in semiconductor manufacturing and detailed scheduling of printed wiring board assembly in surface mount technology lines are discussed. Then, the medium-term aggregate production planning in a production/assembly facility of a consumer electronics supply chain is described; and finally, the coordinated aggregate planning and scheduling of the manufacturing and supply of parts and production of the finished products is presented. The decision variables are defined, and the MIP modeling frameworks are provided. Two decisionmaking approaches are discussed and compared: an integrated (simultaneous) approach, in which all required decisions are made simultaneously using a complex, large monolithic MIP model; and a hierarchical (sequential) approach, in which the required decisions are made successively using the hierarchies of simpler and smaller-sized MIP models. The paper also highlights the research on stochastic MIP applications to the planning and scheduling in electronics supply chains with disrupted material and information flows due to natural or man-made disasters.