An optimization algorithm for cutting stock problems in the TFT-LCD industry

Due to lack of efficient approaches of mixed production, the present production approach of the TFT-LCD industry is batch production that each glass substrate is cut into LCD plates of one size only. This study proposes an optimization algorithm for cutting stock problems of the TFT-LCD industry. The proposed algorithm minimizes the number of glass substrates required to satisfy the orders, therefore reducing the production costs. Additionally, the solution of the proposed algorithm is a global optimum which is different from a local optimum or a feasible solution that is found by the heuristic algorithm. Numerical examples are also presented to illustrate the usefulness of the proposed algorithm.     

Perturbation analysis for production control and optimization of manufacturing systems

We use stochastic fluid models (SFM) to capture the operation of threshold-based production control policies in manufacturing systems without resorting to detailed discrete event models. By applying infinitesimal perturbation analysis (IPA) to a SFM of a workcenter, we derive gradient estimators of throughput and buffer overflow metrics with respect to production control parameters. It is shown that these gradient estimators are unbiased and independent of distributional information of supply and service processes involved. In addition, based on the fact that they can be evaluated using data from the observed actual (discrete event) system, we use them as approximate gradient estimators in simple iterative schemes for adjusting thresholds (hedging points) on line seeking to optimize an objective function that trades off throughput and buffer overflow costs.     

Optimal cycle production of a manufacturing system subject to deterioration

A single part type, single machine, fluid model manufacturing system is considered. The machine is subject to a deterministic deterioration process, which depends on the operation rate. The objective is to minimize a long term average cost index which penalizes inventory surplus and backlog. The optimal policy determined presents some similarities with the policy conjectured optimal in the past for a similar Markovian formulation. The considered problem can be applied to several real contexts, and not just from the manufacturing domain, as briefly discussed in the paper.     

大型调水项目生产调度系统平台研究与设计

当前,大型调水项目生产调度系统由水量调度、工程管理、信息监测和综合办公等众多业务子系统组成,各子系统间已能实现数据层的信息交换,但在应用交互层面则各自相对独立。在实际的调度生产过程中,调度生产人员岗位角色不同决定了其在系统中所使用的功能与权限也不同。各项生产调度功能分散在不同的子系统中,需要调度生产人员在多个系统间来回切换操作,既繁琐又容易发生误操作,整体上不便于调度生产人员使用。本文以南水北调东线山东段工程生产调度系统开发设计为实例,就大型调水项目生产调度系统的建设展开分析与讨论。梳理了各岗位对应的功能与职责,设计出了适合调水项目生产调度的信息系统,降低了系统对用户的使用门槛,同时也提高了生产效率。     

An advanced order acceptance model for hybrid production strategy

Competitors stand out through commitment to providing excellent customer service. Many organizations strive to promote their order promising system to generate more reliable quotes with quantity and due date constraints. This paper develops a Capable-to-Promise (CTP) based Order Acceptance Model (OAM) for a Hybrid Production Strategy (HPS) based on the positioning of the Customer Order Decoupling Points. The proposed model allocates the uncommitted availability and planned production receipts to current and anticipation of future needs. A Mixed-Integer Linear Programming (MILP) is developed to determine the optimal order quantities based on the resource availability. The proposed model efficiently mitigates the risk of not being reliable in the commitments due to discrepancies between the real and unused quantities. The CTP based OAM is compatible with a HPS with both make-to-order (MTO) and make-to-stock (MTS). The presented model encompasses four steps. First, demands for MTO products are collected in batches on daily basis and a forecasting model is applied to predict orders for MTS products. Secondly, the quantity-based Revenue Management approach is used to prioritize orders. Afterwards, the optimization model assesses the availability of resources in order to produce collected orders. The final step is to accept valuable orders based on the resource availability. In order to illustrate the applications of the modeling approach, two case studies are provided.     

Teamwork in production: Implementation,its determinants,and estimates for German manufacturing

The progressive use of teamwork as an element of workplace practices orients researchers to dedicate important efforts to study the phenomenon and its depths. Although team research has focused on a large variety of aspects—human, psychological, positional, technical, and economico‐strategic—less is known about the factors influencing or determining the incidence of such concepts. Implementation rates and the degree of spreading, as well as variables mentioned by previous studies as determinants, were tested on a sample of 1,298 manufacturing firms located in Germany. The results show that almost 2/3 of manufacturing establishments use teamwork in production and, on average, more than 50% of employees are involved in normally four‐ to nine‐person teams. The results of this study also sustain the initial hypothesis on the positive relationship among flexibility, complexity, new products, organizational concepts, and teamwork implementation in production. Theoretical and practical implications of the findings are discussed. © 2010 Wiley Periodicals, Inc.     

High level planning and control: An IDEF0 analysis for airframe manufacture

This paper presents an overview of a high level planning and control system (HLPCS) designed to permit CAD/CAM integration of the manufacturing processes of a generic airframe manufacturing facility. This analysis was performed in part under the direction of the United State Air Force Integrated Computer Aided Manufacturing Program (project priority 6104). The analysis was conducted through the design/communication tool of IDEF₀ (ICAM definition language). This paper will therefore rely heavily on discussions utilizing IDEF₀. The concepts of the HLPCS will be discussed, the aspects of the system enhancements that encourage integration will be highlighted, and conclusions regarding system improvements will be identified.     

Agility and production flow layouts: An analytical decision analysis

The term ‘agile manufacturing’ has referred to operational aspects of a manufacturing company concerning their ability to produce customized products at mass production prices and with short lead times. A core issue faced within agile manufacturing is the need for appropriate and supporting production and operations systems. Many design dimensions of agility and agile manufacturing exist. To help attain this goal for integrating the many design dimensions, operations infrastructure and capacity must be carefully planned to manage production flow, and thus production layout planning takes on an increasingly important role. Given the importance of these dimensions in response to agility, this paper seeks to make a contribution by providing insights into a decision aid for evaluating production flow layouts that support and enhance the agile manufacture of products. Layout design has a significant impact on the performance of a manufacturing or service industry system and has been an active research area for many decades. Strategic evaluation of production layouts requires consideration of both qualitative and quantitative factors (managerial, organizational, and technical). This paper makes use of the Analytical Network Process (ANP) which captures interdependencies among different criteria, sub-criteria and dimensions, an evident characteristic of production flow layouts in complex agile manufacturing environments. An application case study exemplifying the practical usefulness of this type of model describes how management, after implementation of the model, made a mid-course correction related to the production layout initially selected.     

An optimization platform for Poland's power sector considering air pollution and health effects

The article demonstrates the features and applicability of the πESA platform designed for optimization of the Poland's power sector considering air pollution and health effects. πESA is comprised of: a bottom-up energy-economic model TIMES-PL, an air quality modelling system Polyphemus and a module for assessment of environmental and health impacts MAEH. It has been designed as a web application employing computational resources of the ZEUS cluster of the PL-Grid infrastructure. The results show, that the impact of carbon prices on the fuel and technological power generation structure is much stronger as compared to impact of fuel prices. Future PM emissions from the centralized power and heat generation sector do not differ much irrespective of energy scenario considered. For analysed cases, the statistical life expectancy in Poland due to long-term exposure to PM_2.5 air pollution is reduced on average by approx. 183 days. That gives over 12 million years lost for all cohorts included in the analysis.     

An optimal batch size for a production system operating under periodic delivery policy

A manufacturing system that procures raw materials from suppliers in a lot and processes them into a finished product is considered in this research. An ordering policy is proposed for raw materials to meet the requirements of a production facility which, in turn, must deliver finished products demanded by outside buyers at fixed points in time. First, a general cost model is formulated considering both raw materials and finished products. Then, using this model, a simple procedure is developed to determine an optimal ordering policy for procurement of raw materials, and the manufacturing batch size, to minimize the total cost of meeting customer demands in time. The dependent relationships between production batch size and rawmaterial purchasing quantity, and various delivery patterns considered in recent literature are critically reviewed. The quality of the solution is evaluated. Numerical examples are provided.     

粒子群算法在生产物流调度中的应用研究

以提高柔性制造系统（FMS）的生产效率为目标,提出了基于粒子群算法（PSO）的AGV动态调度策略。在PSO中采用三维向量的编码方式,解决了AGV资源分配与任务排序的问题,对编码后的粒子经过速度-位移计算后进行解码,通过读取数据库表得到AGV的运行时间来计算目标函数。并且提出了浮动的目标函数法,以使各AGV的任务均匀,总体最优。最后将该算法嵌入到FMS仿真实例模型中,实时进行AGV的任务调度优化,整个FMS加工任务的总完成时间较优化前缩短了12.1%,证实了算法的有效性。     

Machine planning for manufacturing: dynamic resource allocation and on-line supervisory control

In this paper*, we provide tools for integrating machine planning and manufacturing. Specifically, we show how assembly trees can be coded into operators for machine planners and how machine planners can represent flow-lines, assembly and job-shop choices. We provide a polynomial-time algorithm for succinctly combining multiple plans; the resulting plan can be expressed as four matrices that are equivalent to a Petri net. We also provide a dynamic supervisory controller that can execute a single plan or switch between multiple plans as real-time conditions change.     

An alternative use of the Riccati recursion for efficient optimization

In optimization routines used for on-line Model Predictive Control (MPC), linear systems of equations are solved in each iteration. This is true both for Active Set (AS) solvers as well as for Interior Point (IP) solvers, and for linear MPC as well as for nonlinear MPC and hybrid MPC. The main computational effort is spent while solving these linear systems of equations, and hence, it is of great interest to solve them efficiently. In high performance solvers for MPC, this is performed using Riccati recursions or generic sparsity exploiting algorithms. To be able to get this performance gain, the problem has to be formulated in a sparse way which introduces more variables. The alternative is to use a smaller formulation where the objective function Hessian is dense. In this work, it is shown that it is possible to exploit the structure also when using the dense formulation. More specifically, it is shown that it is possible to efficiently compute a standard Cholesky factorization for the dense formulation. This results in a computational complexity that grows quadratically in the prediction horizon length instead of cubically as for the generic Cholesky factorization.     

Joint admission,production sequencing,and production rate control for a two-class make-to-order manufacturing system

Today's manufacturing industry faces a number of challenges related to the rapid delivery of products with a high degree of variety. Striking a balance between the effectiveness in capacity utilization and the rapidness in order-fulfillment is a substantial challenge for manufacturing companies. This work aims to provide a theoretical basis from which to address this practical question. To this end, we address the problem of coordinating the admission, production sequencing, and production rate controls for a two-class make-to-order manufacturing system. Formulating the problem as a Markov decision process model, we identify the structural properties of optimal control policies under both discounted and average profit criteria. We show that the cμ rule is optimal for production sequencing and the optimal admission and production rate control policies can be characterized by the state-dependent threshold levels, provided that the production times are not associated with customer class. We also show that the optimal production rates are monotone in the system state, as in the case of a single class queueing system, and that the lower priority class can be preferred to the higher priority class in order admission under a certain condition on the system parameters. Our numerical study demonstrates that a considerable economic benefit can be achieved if the production rate is dynamically controlled between the minimum and maximum rates rather than fixed to the mean rate of these values. Finally, we present a heuristic policy that is described by linear switching functions for the control of order admission and a selection rule for the control of production rate. We compare the performance of our heuristic to the optimal policy using a numerical experiment, revealing that the heuristic provides near optimal solutions to test example problems and is robust to the system parameters.     

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.     

An optimization algorithm for shape analysis of regular polygons

Machine vision has the potential to impact both quality and productivity significantly in computer integrated manufacturing due to its versatility, flexibility, and relative speed. Unfortunately, algorithm development has not kept pace with the advances in vision-hardware technology, particularly in the areas of analysis and decision making. The specific subject of this investigation is the development of a machine-vision algorithm for the dimensional checking, pose estimation, and overall shape verification of regular polygonal objects (e.g., surface-mounted electronic components and fastener heads). Algorithmically, the image boundary data is partitioned inton segments, and then a non-ordinary least squares technique is used to find the best fitting polygon. The algorithm is well-suited for online implementation in an automated environment due to its flexibility and demonstrated speed.     

A DSS for production planning focused on customer service and technological aspects

Production planning and control in manufacturing systems cover several aspects, at different hierarchical levels, including decisions on production and inventory quantities, resource acquisition, production allocation and sequencing. We consider a problem that is typical of companies that manufacture products in production plants placed in different production areas worldwide. A solution framework for the production allocation and balancing problems based on mathematical programming is proposed. Its computational efficiency is improved using techniques from constraint programming, in order to make it possible to solve real world instances of the problems. An industrial test case is used as a benchmark to prove the effectiveness of the proposed approach.     

An e-health platform for the elderly population: The butler system

The Butler system is an e-health platform designed to improve the elderly population’s quality of life. The Butler system has three applications diagnostic, therapeutic and playful. The objective of this work is to present the influence of the use of the platform on elderly users’ mood states and the degree of acceptance. These measures were assessed through visual analogical scales before and after the platform use, with the outcome measures MANOVAS analyses were performed. Seventeen users (from 58 to 79 years old) completed four sessions with the system; they could choose which technological resources they used in each session. The results showed that after using the system, the participants’ insensitive emotions increased and their negative ones decreased. In addition, they obtained high levels of satisfaction, low levels of subjective difficulty and would recommend Butler to other users. Therefore, the results indicate that Butler might be an effective system for improving emotional states in elderly population.