A framework for modern manufacturing economics

Modern manufacturing economics is an interdisciplinary research subject which deals with the cycles of performance measurement, cost estimation, and decision analysis that are enmeshed with quantification of ill-structured benefits of advanced manufacturing technologies (AMT). This paper proposes a framework of modern manufacturing economics by examining recent research trends of AMT economics. It underscores integrated, quantitative, global, and strategic studies of AMT economics.     

Jobshop lot streaming with routing flexibility,sequence-dependent setups,machine release dates and lag time

Lot streaming is a technique of splitting production lots into smaller sublots in a multi-stage manufacturing system so that operations of a given lot can overlap. This technique can reduce the manufacturing makespan and is an effective tool in time-based manufacturing. Research on lot streaming models and solution procedures for flexible jobshops has been limited. The flexible jobshop scheduling problem is an extension of the classical jobshop scheduling problem by allowing an operation to be assigned to one of a set of eligible machines during scheduling. In this paper we develop a lot streaming model for a flexible jobshop environment. The model considers several pragmatic issues such as sequence-dependent setup times, the attached or detached nature of the setups, the machine release date and the lag time. In order to solve the developed model efficiently, an island-model parallel genetic algorithm is proposed. Numerical examples are presented to demonstrate the features of the proposed model and compare the computational performance of the parallel genetic algorithm with the sequential algorithm. The results are very encouraging.     

A study on the performance of scheduling rules in buffer-constrained dynamic flowshops

Most studies on scheduling in manufacturing systems using dispatching rules deal with jobshops, while there are only few reports dealing with dynamic flowshops. It is known that the performance of many dispatching rules in dynamic jobshops is different from that in dynamic flowshops. Moreover, many research reports assume that there are no buffer constraints in the shop, and even those reports dealing with buffer-constrained shops present the evaluation of existing dispatching rules for unconstrained shops in the context of buffer constraints with the consideration of a limited number of objectives of scheduling. In this study, we deal with the problem of scheduling in dynamic flowshops with buffer constraints. With respect to different time-based objectives, the best dispatching rules for scheduling in unconstrained shops have been identified from the existing literature. In addition, two new dispatching rules specially designed for flowshops with buffer constraints are proposed. All dispatching rules under consideration are evaluated in dynamic flowshops with buffer constraints on the basis of an extensive simulation study covering different levels of buffer constraints, shop load or utilization, and missing operations in flowshops. The proposed rules are found to perform better than the existing dispatching rules in buffer-constrained flowshops with respect to many measures of performance.     

QQ Models: Joint Modeling for Quantitative and Qualitative Quality Responses in Manufacturing Systems

A manufacturing system with both quantitative and qualitative (QQ) quality responses (as a QQ system) is widely encountered in many cases. For example, in a lapping process of the semiconductor manufacturing, the quality of wafer’s geometrical characteristics is often measured by the total thickness variation as a quantitative response and the conformity of site total indicator reading as a binary qualitative response. The QQ responses are closely associated with each other in a QQ system, but current methodologies often model the two types of quality responses separately. This article presents a novel modeling approach, called “QQ models,” to jointly model the QQ responses through a constrained likelihood estimation. The QQ models can jointly select significant predictors by incorporating inherent features of QQ systems, leading to accurate variable selection and prediction. Both simulation studies and a case study in a lapping process are used to evaluate the performance of the proposed method. Supplementary materials to this article are available online.     

Dispatching rules for scheduling in assembly jobshops - Part 2

In this part of the paper, we present the development and evaluation of dispatching rules for scheduling in jobshops manufacturing multi-level assembly jobs with the performance measures reated to tardiness. We present a new definition of 'operation due date' in the context of assembly jobs and use it in the development of dispatching rules. A simulation study is carried out to evaluate the performances of the existing and the proposed dispatching rules with respect to different measures of tardiness. We also measure their performances with respect to different measures of flowtime and staging delays. The results of the study indicate that the proposed rules perform better than the existing rules.     

Evaluation of Corporate Sustainability

As a consequence of an increasing demand in sustainable development for business organizations, the evaluation of corporate sustainability has become a topic intensively focused by academic researchers and business practitioners. Several techniques in the context of multiple criteria decision analysis (MCDA) have been suggested to facilitate the evaluation and the analysis of sustainability performance. However, due to the complexity of evaluation, such as a compilation of quantitative and qualitative measures, interrelationships among various sustainability criteria, the assessor’s hesitation in scoring, or incomplete information, simple techniques may not be able to generate reliable results which can reflect the overall sustainability performance of a company. This paper proposes a series of mathematical formulations based upon the evidential reasoning (ER) approach which can be used to aggregate results from qualitative judgments with quantitative measurements under various types of complex and uncertain situations. The evaluation of corporate sustainability through the ER model is demonstrated using actual data generated from three sugar manufacturing companies in Thailand. The proposed model facilitates managers in analysing the performance and identifying improvement plans and goals. It also simplifies decision making related to sustainable development initiatives. The model can be generalized to a wider area of performance assessment, as well as to any cases of multiple criteria analysis.     

Quasi-quantitative measures of research performance: An assessment of construct validity and reliability

This paper argues that research performance is essentially a multidimensional concept which cannot be encapsulated into a single universal criterion. Various indicators used in quantitative studies on research performance at micro or meso-levels can be classified into two broad categories: (i) objective or quantitative indicators (e.g. counts of publications, patents, algorithms or other artifacts of research output) and (ii) subjective or qualitative indicators which represent evaluative judgement of peers, usually measured on Likert or semantic differential scales. Because of their weak measurement properties, subjective indicators can also be designated as quasi-quantitative measures. This paper is concerned with the factorial structure and construct validity of quasi-quantitative measures of research performance used in a large-scale empirical study carried out in India. In this study, a reflective measurement model incorporating four latent variables (R & D effectiveness, Recognition, User-oriented effectiveness and Administrative effectiveness) is assumed. The latent variables are operationalized through thirteen indicators measured on 5-point semantic differential scales. Convergent validity, discriminant validity and reliability of the measurement model are tested through LISREL procedure.     

高端测长仪器设计原则在步距规校准仪设计中的应用

制造和测量过程的不断迭代是提升产品性能的关键,目前高端仪器自主研发能力不足使我国高端制造业的发展受到了制约.长度计量仪器是保障制造业量值溯源准确性的重要基础之一,本文以步距规校准装置的研制过程为例,介绍阿贝原则、最小变形原则、最短测量链原则在高端长度计量仪器设计中的具体应用,为高端长度计量仪器的研制提供技术借鉴,推动我...     

冷媒气体泄漏率的定量分析

工业上一般使用标准漏孔对冷媒检漏仪进行定性检测,由于它的便捷性而得到广泛使用。近年来,对标准漏孔的溯源方式和校准方法进行探索逐渐进入人们的视野,冷媒气体泄漏率的定量分析和测量过程的不确定度评估定量分析就显得尤为重要。通过建立数学模型,对标准漏孔在测量过程中影响测量不确定度的因素进行分析和量化。最后通过实验验证,测量结果的相对扩展不确定度约为4%,可以满足了泄漏率量值传递过程中10%的要求。     

Measurement accreditation

Reliable measurement underpins most of the activities of mankind, including manufacturing, service industries and the health service. For example, measuring instruments are used throughout manufacturing processes to ensure the quality of the product is satisfactory. It is essential for international trade that all measuring instruments throughout the world should be based on a compatible system of measurement; this is achieved by calibration and traceability. Traceability is the process by which measurements are related through an approved chain of comparisons to national and international standards. This paper describes the techniques used in the assessment of electrical measurement laboratories so as to provide assurances that the chain of measurement traceability is unbroken     

Measuring long-term performance of a manufacturing firm using the Analytic Network Process (ANP) approach

This paper provides a multicriteria performance measurement model to measure a manufacturing firm's performance in terms of areas of success, which can be defined as critical areas in generating revenues and controlling costs in the operations of a manufacturing firm. In developing the performance measurement model, the Analytic Network Process (ANP) approach is used. The ANP approach, which is the general form of the Analytic Hierarchy Process (AHP) methodology, is recommended when independence among different elements of a system assumption is violated. In a manufacturing system, the system's attributes are interrelated. Furthermore, the relative importance of these attributes with respect to each other and their contribution to the overall performance are affected by the competitive strategies applied by the manufacturing firms. The performance evaluation model developed here incorporates the competitive strategies and interdependence between the system attributes in its hierarchical structure and achieves a more realistic and accurate representation of the firm's long-term performance.     

Dispatching rules for scheduling in assembly jobshops - Part 1

Research on jobshop scheduling has tended to concentrate on the development of dispatching rules for jobs that are independent, i.e. single-component jobs. However, in real-life situations, many jobs involve assembly operations that require scheduling of multiple components through the jobshop where both serial and parallel operations take place. In this two-part paper, we consider the problem of scheduling in assembly jobshops, i.e. jobshops that manufacture multi-level assembly jobs. The development of new and efficient dispatching rules with a view to address various measures of performance related to flowtime and staging delay of jobs is first undertaken. A new concept, called 'operation synchronization date' is introduced and made use of in the new dispatching rules. The best existing dispatching rules and the proposed dispatching rules are relatively evaluated by an exhaustive simulation study. The results indicate that the proposed rules emerge to be superior to the existing ones for most measures of performance.     

Design of an FMS decision support system

Flexible manufacturing system (FMS) is an integrated system consisting of computer numerical control machine tools and automated material handling system controlled by an overall control computer system. The FMS design is broken down into strategic, tactical and operational level designs. This research is concerned with the development of a decision support system for the design of FMS (FMSDDS. Simulation is used as a primary analysis tool, making the DSS capable of solving problems at all three levels. The decision making ability is provided by a multi-attribute utility model which accounts for both quantitative and qualitative factors that affect a decision. The FMSDSS is implemented using three routines: input, analysis, and output. The input routine helps the user to select feasible FMS configurations interactively. The analysis routine consists of a generalized FMS simulation model. This routine analyses the FMS alternatives selected and provides the information required for the output analysis. The qualitative and quantitative measures of performance that have to be considered for decision making are handled by the output routine. It also combines performance measures of different units such as time and cost. The DSS is modular and hence future enhancements can be readily added.     

Theory of constraints in a service application: The Swine Graphics case

Being affected from high technology, modern manufacturing systems have become more complex which means that performance factors of both individuals and manufacturing systems have become more critical due to the overloading of cognitive and decision-making tasks. In addition to this development, the classical performance measurement systems are insufficient to measure cognitive performance and the new measurement systems are needed. But converting the abstract factors of cognition to quantitative models is very difficult and complicated. In this paper, developing quantitative models for determination of cognitive performance factors is studied using the combination of cognitive mapping technique and the analytical hierarchy process in fuzzy theory to identify these factors, express and classify them quantitatively. The pairwise comparison matrices are constructed from cognitive maps, converted to fuzzy numbers using a scale, and the subjectiveness of decision-makers is prevented. Also, more accurate weights are obtained and the monitoring levels of performance factors are suggested. An example in Flexible Manufacturing Systems is provided throughout the paper in order to explain the concepts and discussion.     

The analysis of feature-based measurement error in coordinate metrology

Coordinate measurement systems (CMSs) dominate the dimensional control and diagnostics of various manufacturing processes. However, CMSs have inherent errors caused by the lack of a tracing ability for some of the measured part features. This is important for product inspection and process variation reduction in a number of automated manufacturing systems, such as for example the automotive body assembly process. The lack of a feature tracing ability means that instead of measuring a given feature, the CMS may actually measure the area around the selected feature. In this paper, a principle for the part feature tracing ability and the resultant feature-based measurement error analysis are developed to estimate the aforementioned deficiencies in the CMSs. The impact of feature type and part(s) positional variation on the feature-based measurement error is explored. The proposed approach is applicable to both contact and non-contact CMSs including both mechanical and optical coordinate measuring machines An analysis of the error for different measurement algorithms is presented. We show that the developed feature-based measurement error can have a significant impact on the measurement accuracy and hence on process control and the diagnostic algorithms currently used in manufacturing. A feature-based error map and error compensation approach are also developed and presented. Simulations, experimental results and two industrial case studies illustrate the proposed method.     

Human reliability analysis—Taxonomy and praxes of human entropy boundary conditions for marine and offshore applications

This is the first stage towards the development of a human reliability model called human entropy (HENT). The paper presents qualitative and quantitative taxonomies and praxes of performance shaping factors (PSF) for Marine and Offshore operations. Three structured and guided expert elicitation methods were used in this study. The experts interrogated accident reports and databases from which the generic root causes of failures/accidents in operations are determined. The elicitations led to the development of 9 qualitative and quantitative human influencing factors, which are called Human Entropy Boundary Conditions (HEBC). Further explications of the 9 HEBC gave birth to 137 quantifiable explanatory variables, which are called hypothetical constructs (HyC). The HyCs are used to identify potential risks due to shrinkages in safety standards. Human entropy is a detour from traditional human error and was used as a result of tripartite human failure modes; error, local rationality and extraneous acts, all of which signify disorderliness and are seemingly inevitable in maritime operations. The praxes and scaling of HEBC was developed as guidance towards a practical oriented HRA and provide inputs for measuring human disorderliness in maritime operations.     

水中石油类污染物的光纤荧光在线测量技术研究

根据水中石油类污染物质的光谱特性,采用荧光光谱技术,结合光纤传感技术和CCD探测技术,研制了一种可用于现场测量水中石油类污染物质的荧光光谱测量仪器。鉴于现场环境的特殊性,设计了水中自动取样预处理系统,可以实现真正意义上的实时分析,方便了现场操作。通过现场实验和性能测试,证实了其可行性,可以对水中石油类污染物质进行现场测量,从而进行污染物质的定性识别与定量分析,为水中污染物质监测提供了新的技术手段。     

Developing performance measurement system for Internet of Things and smart factory environment

To cope with large fluctuations in the demand of a commodity, it is necessary for the manufacturing system to have rapid reactive ability. This requirement may be secured by performance measurement. Although manufacturing companies have used information systems to manage performance, there has been the difficulty of capturing real-time data to depict real situations. The recent development and application of the Internet of Things (IoT) has enabled the resolution of this problem. In demonstration of the functionality of IoT, we developed an IoT-based performance model consistent with the ISA-95 and ISO-22400 standards, which define manufacturing processes and performance indicator formulas. The development comprised three steps: (1) Selection of the Key Performance Indicators of the Overall Equipment Effectiveness (OEE), and the development of an IoT-based production performance model, (2) Implementation of the IoT-based architecture and performance measurement process using Business Process Modelling and (3) Validation of the proposed model through virtual factory simulation. We investigated the effect of the IoT-workability on the OEE, based on the final results of the simulation, both for the planned and actual productions. The simulation results showed that the proposed model represented the timestamp data acquired by IoT and captured the entire production process, thus enabling the determination of real-time performance indicators.     

Manufacturing productivity improvement using effectiveness metrics and simulation analysis

Traditional productivity metrics, such as throughput and utilization rate, are not very helpful for identifying the underlying problems and opportunities for productivity improvement in a manufacturing system. In this paper, a systematic methodology is presented for productivity measurement and analysis at the factory level. Metrics of Overall Equipment Effectiveness (OEE) and Overall Throughput Effectiveness (OTE) are introduced and developed, respectively, for rigorous and quantitative measurement of equipment and system productivity. These metrics are integrated with computer simulation to facilitate rapid analysis of equipment and manufacturing system productivity, and the investigation of productivity improvement opportunities. The results of this research make possible the representation of factory level productivity or overall factory effectiveness by OTE, and the use of OTE for quantitative benchmarking and comparison of the productivity of various factories. A real-world manufacturing case study is reported to demonstrate how to employ these techniques to improve manufacturing productivity.     

Conceptions and operational use of value and waste in lean manufacturing – an interpretivist approach

In this article, we explore how the key concepts of lean manufacturing, value, value adding and waste are conceived and operationally used by Lean trainers in operational work processes. A comparative case study with a mixed method approach, using an explanatory sequential design, was conducted. This means that a set of quantitative data were collected, which was followed by the collection of qualitative data with the purpose of explaining and understanding the quantitative measures. An interpretivist approach is used as a framework, which implies a perspective on contemporary operations management paradigms, such as lean manufacturing, as a continuous construction of inter-subjective experiences. What becomes evident in the empirical findings is that there are both similarities and differences in the Lean trainers conceptions and use of value adding and waste. The similarities and differences can be explained by variations in two dimensions: (a) the character of the work process, which ranges between mechanical and craftsmanship, and (b) Lean trainers approach to key concepts, which ranges between being rule-based and reflective. By using a research design where the concepts of value adding and waste were used simultaneously, and adopting an interpretivist approach on lean manufacturing, we were able to reveal conditions that in other cases remain hidden.