The throughput rate of serial production lines with deterministic process times and random setups: Markovian models and applications to semiconductor manufacturing

We conduct exact analysis of serial production lines with deterministic service durations and various classes of random state-dependent setups between customers. Our focus is on assessing the production rate, or just-in-time (JIT) throughput. We demonstrate that such systems can be modeled as a Markov chain and consider various types of setups inspired by clustered photolithography tools in semiconductor manufacturing. We deduce when exact closed form expressions for the production rate are possible and when a numeric solution to the Markov chain balance equations are required. As these systems have shown promise for modeling process bound clustered photolithography tools, we study their accuracy versus detailed simulation for predicting the tool throughput. Various practical features such as the capacity of a pre-scan buffer and batch customers (to model wafer lots) are investigated.     

Systems Support of Just-In-Time Manufacturing

In the current business environment, many organizations are turning to just-in-time (JIT) and total quality control (TQC) techniques to compete as effectively as possible. The MIS department can make an important contribution to the success of JIT by ensuring that the computer system supports its concepts effectively. To do this, however, MIS managers must understand exactly what a JIT system should and should not do. This article discusses the differences between JIT and traditional manufacturing and shows how computer systems can enhance the successful use of JIT techniques.     

Design of a synchronous manufacturing system with just-in-time production (SMS/JITP)

One of the goals of a manufacturing system is to minimize the cost of production. A significant source of manufacturing cost is attributable to material handling. The sources of material handling cost include equipment, labor, work-in-process, and floor space. One approach to reduce material handling cost is through the implementation of synchronous manufacturing with just-in-time production. Although, the concept of a synchronous manufacturing is known, techniques to design and plan such systems are yet to be formalized. In this paper, a quantitative modeling framework for the design and analysis of a synchronous manufacturing system with just-in-time production is presented. The approach is composed of principles and techniques drawn from scheduling, layout planning, material handling, and computer simulation.     

A systematic modelling and simulation approach for JIT performance optimisation

Robust computer aided simulation and modelling tools help to visualise, analyse and optimise complex production processes with a reasonable amount of time and investment. A review of the literature shows that simulation and modelling have not been extensively applied in just-in-time (JIT) manufacturing environments. Also there remains a lack of a comprehensive mechanism to identify the most significant JIT drivers for the purpose of system process optimisation. The prime objective of this study is to close this gap by applying computer based simulation tools and linear mathematical modelling to identify the impact of selected key JIT parameters on performance in an automotive component-manufacturing environment. Research shows that variables such as inconsistent task distribution, variation on operator performance, misconception of total quality management philosophy and lack of set-up time elimination plans disrupt ideal JIT production. In this study, ProModel simulation and modelling software is used to model and simulate different experimental scenarios in order to understand and quantify the impact of selected input key JIT variables on objective functions (i.e. process time and takt time). The outcome is a robust mathematical model that highlights the significance of JIT drivers in the manually operated mixed-model assembly lines.     

An integrated JIT--PQD model for enhancing buyer--supplier linkage (revised version)

Price-quantity discount (PQD) is when suppliers often reduce the unit-purchasing price for large orders to increase their benefits. However, with the adoption of just-in-time (JIT) philosophy, buyers are encouraged to purchase material in small lots to synchronize production with deliveries. Thus, buyers find it difficult to obtain the benefits from both JIT and PQD simultaneously. This paper proposes an integrated JIT--PQD model for enhancing buyer--supplier linkage in which buyers need not abandon either JIT and PQD but suppliers can increase their benefits. Furthermore, the integrated JIT--PQD model allows resource constraints to be added by the decision-maker as deemed appropriate in real-world situations. To demonstrate the usefulness of the proposed method an illustrative example is included.     

Simulation analysis of just-in-time feasibility in a manufacturing environment

There is much interest in American industries in the use of just-in-time (JIT) manufacturing to reduce the work-in-progress (WIP) inventory and to increase the quality of the end product. However, while it promises significant results, it may be difficult to justify that management discard an operating MRP system in favor of a philosophy. This paper describes a study conducted in a manufacturing environment for a possible JIT implementation in the production floor and describes the simulation analyses of the operation.     

A framework for quality assessment of just-in-time requirements: the case of open source feature requests

Until now, quality assessment of requirements has focused on traditional up-front requirements. Contrasting these traditional requirements are just-in-time (JIT) requirements, which are by definition incomplete, not specific and might be ambiguous when initially specified, indicating a different notion of "correctness." We analyze how the assessment of JIT requirements quality should be performed based on the literature of traditional and JIT requirements. Based on that analysis, we have designed a quality framework for JIT requirements and instantiated it for feature requests in open source projects. We also indicate how the framework can be instantiated for other types of JIT requirements. We have performed an initial evaluation of our framework for feature requests with eight practitioners from the Dutch agile community, receiving overall positive feedback. Subsequently, we have used our framework to assess 550 feature requests originating from three Open Source Software systems (Netbeans, ArgoUML and Mylyn Tasks). In doing so, we obtain a view on the feature request quality for the three open source projects. The value of our framework is threefold: (1) it gives an overview of quality criteria that are applicable to feature requests (at creation time or JIT); (2) it serves as a structured basis for teams that need to assess the quality of their JIT requirements; and (3) it provides a way to get an insight into the quality of JIT requirements in existing projects.     

Dynamic routing under recurrent and non-recurrent congestion using real-time ITS information

In just-in-time (JIT) manufacturing environments, on-time delivery is a key performance measure for dispatching and routing of freight vehicles. Growing travel time delays and variability, attributable to increasing congestion in transportation networks, are greatly impacting the efficiency of JIT logistics operations. Recurrent and non-recurrent congestion are the two primary reasons for delivery delay and variability. Over 50% of all travel time delays are attributable to non-recurrent congestion sources such as incidents. Despite its importance, state-of-the-art dynamic routing algorithms assume away the effect of these incidents on travel time. In this study, we propose a stochastic dynamic programming formulation for dynamic routing of vehicles in non-stationary stochastic networks subject to both recurrent and non-recurrent congestion. We also propose alternative models to estimate incident induced delays that can be integrated with dynamic routing algorithms. Proposed dynamic routing models exploit real-time traffic information regarding speeds and incidents from Intelligent Transportation System (ITS) sources to improve delivery performance. Results are very promising when the algorithms are tested in a simulated network of South-East Michigan freeways using historical data from the MITS Center and Traffic.com.     

Joust: a platform for liquid software

The authors describe a Java-based platform for liquid software, called Joust, that is specifically designed to support low-level, communication-oriented systems and to avoid the limitations of general-purpose OSs. The authors contrast the platform requirements for communication-oriented liquid software with those of computation-oriented software, identify the limitations of current platforms, and outline the benefits of Joust. They also offer an overview of Scout (the underlying OS upon which Joust is built), its runtime system, and its just-in-time (JIT) compiler     

基于多Agent的JIT软件构架研究

以智能JIT管理软件开发项目为研究背景,阐述基于多Agent的JIT软件构架的研究问题。根据JIT原理构建JIT生产过程构架;使用UML建模工具构建JIT管理软件类构架,将领域构架转化为软件构架,并且应用多Agent技术优化软件构架：构建了JIT系统的Petri网模型,分析了JIT系统的动态特性。通过在智能JIT管理软件开发中的实际应用,证明JIT的过程构架和软件构架是合理的,并取得了良好的效果。     

An integrated artificial neural network-computer simulation for optimization of complex tandem queue systems

This paper presents an integrated artificial neural network-computer simulation (ANNSim) for optimization of G/G/K queue systems. The ANNSim is a computer program capable of improving its performance by referring to production constraints, system's limitations and desired targets. It is a goal oriented, flexible and integrated approach and produces the optimum solution by utilizing Multi Layer Perceptron (MLP) neural networks. The properties and modules of the prescribed intelligent ANNSim are: (1) parametric modeling, (2) flexibility module, (3) integrated modeling, (4) knowledge-base module, (5) integrated database and (6) learning module. The integrated ANNSim is applied to 30 distinct tandem G/G/K queue systems. Furthermore, its superiority over conventional simulation approach is shown in two dimensions which are average run time and maximum number of required iterations (scenarios).     

Ahead-of-time compilation of JavaScript programs

Modern virtual machines for JavaScript use just-in-time (JIT) compilation to produce binary code. JIT compilers cannot perform complex optimizations. In contrast, static compilation has unlimited capabilities for complex optimizing transformations, but it cannot be efficiently applied to dynamic languages, such as JavaScript. In this paper, a general approach to the ahead-of-time compilation of programs in dynamic languages is proposed, and this approach is used for improving two virtual machines JavaScript- Core and V8. In the implementation of the improved JavaScriptCore engine with ahead-of-time compilation, the specifics of using JavaScript programs as a part of locally stored applications for the ARM platform were taken into account. In the V8 engine for the x86-64 platform, the ahead-of-time compilation is implemented by caching an optimized internal representation in a separate file.     

Compiling Java just in time

The Java programming language promises portable, secure execution of applications. Early Java implementations relied on interpretation, leading to poor performance compared to compiled programs. Compiling Java programs to the native machine instructions provides much higher performance. Because traditional compilation would defeat Java's portability and security, another approach is necessary. This article describes some of the important issues related to just-in-time, or JIT, compilation techniques for Java. We focus on the JIT compilers developed by Sun for use with the JDK (Java Development Kit) virtual machine running on SPARC and Intel processors. (Access the Web at www.sun. com/workshop/java/jit for these compilers and additional information.) We also discuss performance improvements and limitations of JIT compilers. Future Java implementations may provide even better performance, and we outline some specific techniques that they may use     

A rule induction approach for determining the number of kanbans in A just-in-time production system

A procedure based on rule induction is presented which can be used to determine the number of kanbans while simultaneously determining the critical factors in a just-in-time (JIT) production system. In particular, the classification and regression tree (CART) technique developed by Brieman et al. [Breiman, L., Friedman, J., Olshen, R. and Stone, C. J., Classification and Regression Trees. Wadsworth, Belmont, CA, 1984.] is used to automatically generate rules from dynamic shop floor data. An example application of the methodology is presented and the advantages of a rule induction approach are explained. The paper concludes with a discussion of future research directions.     

Distributed Reinforcement Learning Control for Batch Sequencing and Sizing in Just-In-Time Manufacturing Systems

This paper presents an approach that is suitable for Just-In-Time (JIT) production for multi-objective scheduling problem in dynamically changing shop floor environment. The proposed distributed learning and control (DLC) approach integrates part-driven distributed arrival time control (DATC) and machine-driven distributed reinforcement learning based control. With DATC, part controllers adjust their associated parts' arrival time to minimize due-date deviation. Within the restricted pattern of arrivals, machine controllers are concurrently searching for optimal dispatching policies. The machine control problem is modeled as Semi Markov Decision Process (SMDP) and solved using Q-learning. The DLC algorithms are evaluated using simulation for two types of manufacturing systems: family scheduling and dynamic batch sizing. Results show that DLC algorithms achieve significant performance improvement over usual dispatching rules in complex real-time shop floor control problems for JIT production.     

Development of an agent-based system for manufacturing control and coordination with ontology and RFID technology

Integrating physical objects with the corresponding enterprise applications any time any where is the essential issue for a real-time enterprise. This study proposes a multi-agent system framework called agent-based manufacturing control and coordination (AMCC) system, a agent-based framework using ontology and RFID technology to monitor and control dynamic production flows and also to improve the traceability and visibility of mass customization manufacturing processes. The capabilities offered by multi-agent systems to respond to RFID events in real-time and a broad class of agent design and coordination issue regarding just in time (JIT) and just in sequence (JIS) manufacturing processes are also exploited in this study. To validate the proposed framework, case study of a bicycle manufacturing company is used to demonstrate how the proposed framework can benefit its JIT production. Finally, an example prototype system is implemented to demonstrate the concept of the proposed framework.     

Two decades of live coding and debugging of virtual machines through simulation

OpenSmalltalk-VM is a virtual machine (VM) for languages in the Smalltalk family (eg, Squeak and Pharo), which is itself written in a subset of Smalltalk that can easily be translated to C. VM development is done in Smalltalk, an activity we call “simulation.” The production VM is then derived by translating the core VM code to C. As a result, two execution models coexist: simulation, where the Smalltalk code is executed on top of a Smalltalk VM, and production, where the same code is compiled to an executable through a C compiler. The whole VM execution can be simulated: the heap is represented as a huge byte array, the VM code is executed as Smalltalk, and the native code generated by the just-in-time (JIT) compiler is executed by a processor simulator. All the Smalltalk development tools, such as the debugger, are then available while simulating. In addition, in simulation, it is also possible to use debugging features such as single stepping in the machine code generated by the JIT compiler. The Smalltalk development tools combined with the simulation debugging features provide developers with a productive environment in which to extend and debug the VM. In this article, we detail the VM simulation infrastructure and report our experiences developing and debugging VM features within it such as the garbage collector and the JIT compiler.     

An efficient frontier for sum deviation JIT sequencing problem in mixed-model systems via apportionment

In this paper, the sum deviation just-in-time (JIT) sequencing problem in mixed-model production systems is studied relating with the discrete apportionment problem together with their respective mathematical formulations. The assignment formulation for the first problem is brieffy discussed followed by the existence of JIT cyclic sequences. Presenting the concise discussion on divisor methods for the discrete apportionment problem, we have proposed two mean-based divisor functions for this problem claiming that they are better than the existing divisors; hence, we found a better bound for the JIT sequencing problem. The linkage of both the problems is characterized in terms of similar type of objective functions. The problems are shown equivalent via suitable transformations and similar properties. The joint approaches for the two problems are discussed in terms of global and local deviations proposing equitably efficient solution.     

An integrated MRP and JIT framework

A new production planning and scheduling framework is developed to address the multi-stage, production-inventory system problem by integrating Material Requirements Planning (MRP) and Just-in-Time (JIT) production. The objective is to find detailed shop-floor schedules, which specify the quantity of an operation to be processed, at what time, and by which machine, so as to minimize total production cost. The integrated system gets rid of the major problems existing in MRP and JIT. First of all, the proposed integrated system incorporates both the scheduling and capacity planning aspects, simultaneously. Secondly, the integrated system eliminates the need to specify planned lead time. Thirdly, the integrated system, unlike MRP, provides detailed shop-floor schedules. Lastly, the integrated system does not have to operate in the level schedule case as in JIT, so it can handle a very general production environment.     

适用单片集成电路封测线的生产计划管理系统

根据单芯片集成电路封测生产线的特点,通过对比分析三种常见的生产计划管理系统:物料需求计划/制造资源计划/企业资源计划、准时制生产方式、约束理论,分析它们的优缺点,并综合这三种不同的生产管理系统,找出一种适合单芯片集成电路封测生产线多品种小批量特点的生产计划管理系统。多品种小批量的生产计划管理可分为三个层次,由单位机关职能部门组成的上层机构,由单位运营部门组成的中层机构,由单位车间等作业部门组成的下层机构,每个层次适用于不同的生产计划管理手段。通过图表,说明这种生产计划管理系统在实际生产中的应用。