Integrating order release control with due-date assignment rules

This study integrates order release control methods with due-date assignment rules and assesses its impact on the accuracy of inter-operation time estimation and performance of due-date assignment. The assessment is made by using an experimental design with three due-date assignment rules, three scheduling rules and three order release models. The three order release models are: (1) Basic model, in which three due-date assignment rules consider the order arrival time as the order release time; (2) Control model, in which three due-date assignment rules integrate with the order release control method developed here; and (3) Adjustment model, in which the control model integrates with the order release control adjustment developed here. Simulation results in this study indicate that integrating the order release control method with due-date assignment rules will significantly enhance not only the accuracy of interoperation time estimation, but also the performance of due-date assignment rules.     

Real-time batch sequencing using arrival time control algorithm

This paper proposes a new feedback control method for batch sequencing in process industries where meeting customer due-date is important. Specifically, short-term batch sequencing for Just-In-Time is solved using an arrival time control approach. An integral controller embedded in each order adjusts the arrival time in real-time using the feedback obtained from a fast-mode simulation of the batch processing system. The applicability of the proposed batch sequencing method for the Penn State University Creamery is studied. Comparison of due-date performance with commonly used dispatching rules is presented. The proposed method has also been tested for general batch processing systems and has been found to produce good, feasible schedules with significantly better performance than the dispatching rules in terms of due-date deviation minimization.     

New dispatching rules for shop scheduling: A step forward

This paper provides a set of new dispatching rules for the minimization of various performance measures such as mean, maximum and variance of flow time and tardiness in dynamic shops. A static rule which minimizes the number of tardy jobs is also proposed. To evaluate these proposed rules, their relative performance is analysed in open job shops and reported in comparison with the standard benchmark rules such as the SPT (shortest process time) and EDD (earliest due-date), popular rules like ATC (apparent tardiness cost) and MOD (modified operational due-date), and the best performing rules in current literature such as RR, PT + WINQ, PT + WINQ + SL and AT-RPT. Thereafter, a comparative analysis of the relative performance of these rules is carried out in job shops (with no machine revisitation of jobs) and flow shops (with missing operations on jobs) in dynamic environments. Based on the simulation study and analysis of results in different manufacturing environments viz. job shops and flow shops, observations and conclusions are made, highlighting some interesting aspects about the effect of routeing on the individual performance of rules.     

Improved customer satisfaction with a hybrid dispatching rule in semiconductor back-end factories

On-time delivery is a vital factor for customer satisfaction in the competitive semiconductor manufacturing industry, and to optimize on-time delivery manufacturers must continuously improve their management of work-in-progress (WIP). However, in undertaking to optimize WIP, managers are also concerned with short cycle times, high throughput, and high utilization. In an attempt to find the most satisfactory solution to these potentially conflicting requirements with regard to WIP, the present study employs fuzzy analytic hierarchy process (AHP) to determine an appropriate set of acceptable WIP deviation levels (AWDLs). These AWDLs are then used in a proposed hybrid dispatching rule to determine the operational priorities of jobs. A simulation model using real-world data is then constructed to examine the proposed mechanism for improving customer satisfaction. The findings of the study confirm that the proposed mechanism is capable of simultaneous consideration of various goals and the achievement of enhanced performances with respect to due-date delivery from semiconductor back-end processes.     

A DUALITY APPROACH TO OPTIMAL DUE-DATE DETERMINATION

This paper considers the problem of determining the optimal constant flow allowance for the CON due-date assignment method. A linear programming formulation of the problem is proposed and the optimal due-date is obtained by solving the LP dual problem.     

Robust scheduling in an advanced planning and scheduling environment

A new scheduling problem that appears in an advanced planning and scheduling (APS) environment is discussed. Under the precondition that all materials are available when needed, the problem is formulated as follows: min N i =1 ( D i - E i )/N subject to D i - C i S 0, for all i , where N is the number of customer orders arriving randomly at the shop during a certain period, D i is the estimated due-date for customer order i , E i is the due-date estimation time for customer order i and C i is the completion time for customer order i . Then, D i and C i are endogenous variables and E i is an exogenous variable. The ability to construct a flexible scheduling process that avoids the need to fix ongoing schedules is essential to all APS systems. Therefore, the concept of a due-date buffer is introduced which is expected to enable the production schedules for each customer order to be flexible at the beginning and gradually become fixed as the processing of the order progresses. A simulation-based scheduling algorithm using the concept of a due-date buffer is developed here and subsequently examined through a series of numerical experiments. The obtained computation results show that the performance of due-date buffers is outstanding with respect to complicated production processes having higher utilizations.     

Due-date setting methodologies based on simulated annealing—an experimental study in a real-life job shop

In this article we present a real-life study of a job shop manufacturing ball screws. The aim of the study is to suggest an efficient scheduling and due-date setting policy for the shop. Three different methodologies for setting parameter coefficients for due-date setting in a job shop are proposed. These methodologies are based on a search algorithm, simulated annealing algorithm, and a combination of simulated annealing algorithm and regression analysis. It is found that the combination of a simulated annealing algorithm with regression analysis provides better due-date estimates in minimizing the root mean square of lateness.     

Performance of real-time distributed arrival time control in heterarchical manufacturing systems

A highly distributed feedback control algorithm for autonomous part entities in heterarchical manufacturing systems is presented in this paper. A difference equation-based model is developed to analyze the discrete time dynamics of the resulting nonlinear control system. Control parameters are found analytically that guarantee that the system is bounded under disturbances. The dynamic response to: (i) changes in due dates; and (ii) the bulk arrival of parts is presented. The ability of the system to exponentially reduce the mean and variance of due-date deviation in the single machine case makes it an attractive option for real-time control of just-in-time production.     

Permutation and non-permutation schedules for the flowline manufacturing cell with sequence dependent family setups

Through the use of an effective simulated annealing algorithm, this paper presents an extensive computational investigation concerning the performance evaluation of non-permutation vs. permutation schedules for the flowline manufacturing cell with sequence dependent setup times. The results show that there are significant improvements made by using non-permutation schedules over permutation schedules regarding completion-time based and due-date based criteria. It is suggested that practitioners could adopt non-permutation schedules to improve their operational efficiency within a reasonable amount of computational effort.     

Behavior of square concrete columns reinforced with Prefabricated Cage System

Behavior of normal strength concrete columns reinforced with a new reinforcement, termed Prefabricated Cage System (PCS) is investigated. A total of 16 small-scale PCS and rebar reinforced column specimens were constructed and tested under monotonic axial displacement. The experimental results indicate that the overall behavior of rebar and PCS reinforced specimens are comparable prior to achieving the peak column load. In general, PCS specimens are more ductile and absorb more energy than similar rebar specimens after the peak load is reached. The effect of different parameters, such as the steel tube thickness, number of longitudinal reinforcements, transverse steel spacing, and crossties on the specimens’ strength and deformation capacity are investigated. A confined concrete model is proposed and used to predict the load–displacement response. The theoretical load–displacement relations obtained from the proposed model are compared with those obtained from the Mander et al. (J Struct Eng 114(8):1804–1826, 1988) confinement model.     

Fast and meta-heuristics for common due-date assignment and scheduling on parallel machines

This study considers common due-date assignment and scheduling on parallel machines. The problem has three decision variables: assigning the common-due-date, allocating jobs to parallel machines, and sequencing the jobs assigned to each machine. The objective is to minimise the sum of due-date assignment, earliness and tardiness penalties. A mathematical programming model is presented, and then two types of heuristics are suggested after characterising the optimal solution properties. The two types of heuristics are: (a) a fast two-stage heuristic with obtaining an initial solution and improvement; and (b) two meta-heuristics, tabu search and simulated annealing, with new neighbourhood generation methods. Computational experiments were conducted on a number of test instances, and the results show that each of the heuristic types outperforms the existing one. In particular, the meta-heuristics suggested in this study are significantly better than the existing genetic algorithm.     

Adaptive scheduling: the use of dynamic due dates to accommodate demand variance in a make-for-stock shop

Results are presented of experiments with a simulation model of an actual make-for-stock shop, in which both the scheduling and due-date updating decision rules were varied and the effect on a cost function observed. A marked interaction between the rules occurred in some cases. One of the due-date updating rules, which does not appear to have been used previously, had the effect of advancing or retarding the due date of a batch as it passed through the shop in response to the difference between the actual and expected demand for the product. This rule was found to perform well when used in combination with a due-date-based scheduling rule.     

订货生产式企业作业任务交货期决策研究

分析了工序时间的随机性特征及其对任务完工期的影响及作业任务交货期决策的重要性，确定任务交货期的方式，指出在工序时间随机性特征条件下，任务交货期应为一个区间，建立了以损失费用最小化为目标的最优交货期时区模型、最优最早交货期模型、最优完工时间偏差控制模型，采用计算机迭代法验证了上述各模型的有效性。     

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

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 real-world 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.     

即时定制生产模式下产品交货期及策略研究

从供应链系统的角度,研究了即时定制生产模式的产品交货期问题,建立了产品交货期数学模型,推导出经济交货期公式,通过敏感性分析,提出了缩短或压缩产品经济交货期的方法,并且从企业的角度,提出了即时定制生产模式下的产品交货期策略.     

A Comparison of Due-Date Selection Rules

In sequencing and scheduling models it is usually assumed that due dates represent exogeneous information. In many practical settings, however, due dates can be discretionary, or at least negotiable. Relatively few studies have incorporated discretionary due dates, and even then the rules proposed for due-date selection have seldom been developed from normative, analytic results. In this research we return to very basic scheduling models in search of fundamental insights and relationships that suggest guidelines for due-date selection in more complicated situations. We exploit some fundamental results from scheduling theory involving the single-machine model in order to compare three basic strategies for due-date selection.     

Demonstration of statistical approaches to identify component's ageing by operational data analysis—A case study for the ageing PSA network

The paper presents some results of a case study on “Demonstration of statistical approaches to identify the component's ageing by operational data analysis”, which was done in the frame of the EC JRC Ageing PSA Network. Several techniques: visual evaluation, nonparametric and parametric hypothesis tests, were proposed and applied in order to demonstrate the capacity, advantages and limitations of statistical approaches to identify the component's ageing by operational data analysis. Engineering considerations are out of the scope of the present study.     

Due-date determination with resequencing

Traditional scheduling and due-date determination models assume that the production system is operating in a static and deterministic environment and that the system carries no workload at each scheduling epoch. In this research we consider a due-date determination model where the scheduler wishes to update the existing schedule when some new jobs have: arrived into the system. In this model, jobs are categorized as either "old" or "new" jobs, where the due-dates of the old jobs are treated as given parameters and those of the new jobs are decision variables. The objective is to minimize the maximum weighted tardiness penalty and the due-date assignment cost. The computational complexity of this model is analyzed, and an efficient algorithm is developed for an important special case.     

A framework to engineer production control strategies and its application in electronics manufacturing

One of the most challenging tasks of companies with complex and discrete production systems is to determine an appropriate production control strategy (PCS). The PCS is crucial, as it influences inventory, costs, and service. We propose a framework to address the most important questions of PCS engineering: limiting work in process, positioning the order penetration point (OPP), and coping with demand uncertainty upstream the OPP. Thereby, uncertain advance demand information in the form of forecasts is considered and desirable characteristics of push and pull strategies are combined. A serial manufacturing system with multiple products, variable processing times, and uncertain advance demand information is examined. The model is formulated as a queuing network model and solved numerically by discrete-event simulation. The framework and a resulting hybrid control strategy are applied to a case study from electronics manufacturing, where a significant improvement potential is identified.