Planning,scheduling and dispatching tasks in production control

"What is the difference between planning and scheduling?" Production control encompasses many tasks performed by humans, three of which are planning, scheduling, and dispatching. In the past, the only criterion that could distinguish between the tasks was that planning is usually on a higher level than scheduling and scheduling is on a higher level than dispatching. Hence, the tasks are often ambiguous, unclear, and subject to speculation. There are few formal studies on the actual tasks of planning, scheduling, and dispatching, and there are no known studies that compare or discuss all three. In this paper it is argued that it is important to understand the differences between the tasks. An action science and ethnographic case study is presented as the empirical basis for the discussion, and the implications for decision support systems in production control tasks are presented.     

A model for integrating process planning and production planning and control in machining processes

The goal of process planning is to propose the routing of a previously designed part and results in a sequence of operations and their parameters. It concerns and requires detailed information about the process. The goal of production planning, on the other hand, is to schedule, sequence and launch the orders introduced on the routing sheet into the job-shop according to the enterprise's strategic goal and the actual conditions of the production plant. The goals, information and decisions taken in process planning and production planning and control are often very different and, because of that, it is very difficult to integrate them.

The objective of this work is to develop a model that can be applied in the future to the development of an integrated process planning and scheduling tool using an integrated definition (IDEF) methodology to design an activity model, which integrates process and production planning in metal removal processes. An activity model will be used to develop a system that allows the user to plan the process and the production at the same time in collaborative engineering work. To design the activity model, a wide range of parts were evaluated and processed in an actual job-shop factory. Several activities were developed in detail to be tested in real cases, and an example of one of them is introduced in this article.     

On the importance of sequencing decisions in production planning and scheduling

We discuss the traditional hierarchical approach to production planning and scheduling, emphasizing the fact that scheduling constraints are often either ignored or considered in a very crude way. In particular, we underline that the way scheduling is carried out is crucial for the capacity constraints on the lot sizes. Usual methods to handle capacity in theory or in practice are reviewed. Finally, we present an approach that tries to overcome these drawbacks by capturing the shop–floor capacity through scheduling considerations.     

Autonomy in production logistics: Identification, characterisation and application

Competitive enterprises have to react fast and flexible to an increasing dynamic environment. To achieve the ability to adapt on these new requirements autonomous cooperating logistic processes seem to be an appropriate method. In order to prove in which case autonomously controlled processes are more advantageous than conventionally managed processes, it is essential to specify what is exactly meant with autonomous control, how autonomous control does differ from conventional control and how the achievement of logistic objectives in autonomously controlled systems can be estimated and compared to the achievement of objectives in conventionally controlled systems. This paper introduces a general definition of autonomous control as well as a definition in the context of engineering science and its meaning in a logistics context. Based on this, a catalogue of criteria is developed to ensure the identification of autonomous cooperating processes in logistic systems and its distinction to conventionally controlled processes. To demonstrate this catalogue, its criteria and the concerning properties are explained by means of an exemplary shop-floor scenario.     

Multilevel optimization algorithms in computer aided production control in process industry

The use of optimization techniques in production control is discussed. Two optimization problems in relation to typical process industry complexes are formulated. A modified version of Tamura's algorithm is reviewed. The promising performance of the computerised algorithms is illustrated by numerical results. DISPATCHER, a practical operative decision support system, is described.     

Integration of process planning and production scheduling based on genetic algorithm

Lacking of flexibility in the traditional workshop production, a genetic algorithm is proposed to implement the integration of process planning and production scheduling. In this paper, the processing routes and processing machine are selected through chromosome crossover and mutation, in order to implement the optimal scheduling of the flexible workshop production. Meanwhile, a performance test about the integration of process planning and production scheduling is implemented, and the results shows that the genetic algorithm is efficient to obtain optimal or near optimal process routes which can meet the requirements of production scheduling.     

Order partitioning and Order Penetration Point location in hybrid Make-To-Stock/Make-To-Order production contexts

Hybrid Make-To-Stock (MTS)/Make-To-Order (MTO) is one of the product delivery strategies which have recently attracted practitioners’ and academicians’ interest to meet requirements of today competitive environment. Two important decisions involved in hybrid MTS/MTO context are order partitioning and determining Order Penetration Point (OPP) location. In this paper, a model is developed to first decide on which product is manufactured upon MTS, which one upon MTO and which one upon hybrid strategy. Then, a fuzzy analytic network process (ANP) is utilized to locate the OPP for the products which are decided to be manufactured upon hybrid strategy. Finally, a real industrial case study is reported to show applicability of the proposed model.     

基于改进型批决策与调度建模的生产计划调度系统的研究

热轧型钢生产工艺复杂,其生产中极易出现由于计划调度安排不当而产生的交货期延误、库存超负荷等问题。针对以上问题研究设计了MES生产计划调度系统,改进了批决策调度策略用于数学建模,利用自适应遗传算法求解生产调度计划。以此为基础,为某热轧企业设计实现了生产计划调度系统,并通过真实的热轧型钢订单、原料、设备等数据,对模型改进前后的计划编制方法进行模拟与比较,验证了利用该改进型批决策与调度模型编制的热轧型钢生产调度计划可节省生产时间、降低设备调度时间,以此来指导热轧型钢的生产可切实减少交货延误和减少库存占用率,并提高企业利润率。     

工艺规则知识管理系统的研究与开发

本文重点阐述了工艺规则知识管理系统的研究与开发原理,论述了通用的基于关系数据库的工艺决策知识模型构建方法。提出了工艺决策产生式规则表示方法,摒弃了传统的利用固定加工方法或加工规则设计数据库字段的方法,有效地保证了系统的通用性和移植性。     

一体化钢铁生产计划系统的研究现状与展望

以钢铁企业生产的背景,叙述了一体化管理在企业管理中的地位,进而综述了钢铁生产工序管理和生产计划理论方法发展趋势,特别指出了生产计划是MES的核心功能,战略管理一体化,多工序一体化和生产计划综合集成方法是今后发展的主要趋势。一体化生产计划应用效果显著,但必须兼顾“目标,管理、技术”三方面问题,研究开发才有成效。     

Software measure in cyber-attacks on production control system

The likelihood of cyber-attacks against information systems and related production control systems has increased. In order to lower the risk of cyber-attacks, OS makers release timely security updates. However, the amount of time that is available for applying patches is limited on production control systems and the possibility of side effects is a concern. Therefore, we focused on the patch application cycle and the period of pretest, and proposed optimal OS measures for production control systems. We presented the method for quantifying the risk of cyber-attacks on production control systems due to security patches not being applied and for expressing the risk as a monetary amount. This method was also proposed for deriving the patch application cycle, the number of applications, and the optimum test duration. We concluded that this method help to understand the patch management and related security measure and to protect production control systems from cyber-attacks.     

A bimodal scheme for multi-stage production and inventory control

This study considers a multi-stage multi-item production plant with its supply chain and customer environment. The production, supply and inventory plan is optimized on a dual-mode basis, under two different information patterns. The short-term plan relies on firm orders received from customers. On the contrary, the long-term plan is based on predicted demands represented by random sequences. In this study, the role of the long-term plan is mainly to impose a final condition set to the short-term plan.     

多节点流水线生产订单接受与调度一体化问题

为了使企业在选择订单时获取最大利润,避免产生惩罚损失,提出了一种流水线生产企业订单接受与调度一体化的决策方法。在该方法中,将订单接受与调度同时规划,建立了以利润最大化为目的,考虑拖期惩罚的决策模型。提出一种新的基于模拟退火过程的启发式求解算法来求解该模型,实例验证了算法的有效性。     

移动机器人运动规划与计算机控制实现

论文针对移动机器人的链式系统提出了一种实时运动规划方法,通过在线更新复合分段常值与多项式输入控制律的系数,来驱使系统到达预定的目标,并将其应用于两伺服直流电机独立控制轮式移动机器人,采用计算机系统以及伺服放大器实现其控制,控制的结果达到了预期的效果。     

Optimal operation of oil and gas production using simple feedback control structures

The purpose of this paper is to describe the control challenges related to optimal operation of oil and gas production wells, and show that optimal operation can be achieved using simple feedback control structures. In particular, we find that conventional feedback control structures can efficiently handle changes in active constraint regions using simple logics such as split-range and selectors. This eliminates the need for complex models to be used in the optimization problem, and in addition eliminates the need to solve numerical optimization problems online. Thus, by using only simple feedback controllers that have been used widely in the oil and gas industry, it has a higher chance of implementation. We demonstrate the use of simple feedback controllers on two application examples; 1) a gas-lift optimization simulation study with a network of six gas-lifted wells, 2) an experimental study of optimal control of electrical submersible pump (ESP) lifted oil wells tested on a large-scale experimental test facility with a full scale ESP and live viscous crude oil.     

Production control: Current developments and future trends

Manufacturing industry is going through a period of unprecedented change as a result of the developments in micro-electronic technology. This is bringing about a transformation not only in hardware, in the form of computer-aided manufacturing, but in the manner in which production is organised and controlled.It is in the latter connection that the present paper sets out to review current developments and future trends. In particular the machine readable bar-code is seen as a key element in extending computerised control to cover not only the machines, but tools, materials and parts and their movement in the development of fully integrated manufacturing systems.As the move towards automation gathers pace it is forecast that manufacturing industry will become more process industry like in form, with consequences for the way in which production is organised and controlled.Finally consideration is given to the manner in which these current developments in the field of production are giving rise to a structural alteration in industrial labour requirements in which, in the future, fewer people will be required but on highly enriched work tasks.     

An analytical approach to improving due-date and lead-time dynamics in production systems

A deterioration of due-date reliability is often attributed by planners to external causes rather than to their own planning behavior. Particularly, planners tend to underestimate the effects of time delays, and may not sufficiently take control actions into account that have been initiated but are not yet demonstrating any effects. Unfavorable dynamic behavior can result if planners react inappropriately to short-term decreases in due-date reliability and, for example, use their intuition to adjust planned lead times. A better understanding is needed of the impact of time delays and lead-time-related adjustments on resulting system behavior and of how often plans and associated work releases should be adjusted in practice.In this paper, two planning and control approaches are modeled and analyzed: First, a production system is modeled in which planned lead times and work input are adjusted periodically if the average lead time deviates from the planned lead time. Second, a production system is modeled in which regulation of lead time towards a planned lead time is accomplished by adjusting the work input. For both approaches, discrete (z-transform) equations are obtained that allow trends in dynamic behavior to be characterized as a function of delays in obtaining production information, and delays in making lead time adjustment decisions and implementing them. Industrial data from a steel-producing company are used to illustrate the potential effects of time delays and of averaging of lead time data, as well as to illustrate how analytical results can be used to guide selection of the adjustment period and of lead time regulation parameters. The analytical approach presented here can be used as a tool for quantifying and guiding improvements in the performance, the robustness, and the agility of production systems. This is of particular interest with respect to cyber-physical technologies such as autonomous data collection and embedded models that present significant future opportunities for reducing delays in decision making and decision implementation.