Modelling process platforms based on an object-oriented visual diagrammatic modelling language

Process platforms have been recognised as a promising means of dealing with product variety while achieving a near mass production efficiency. To assist practitioners to better understand, implement and use process platforms, this study addresses the underlying logic for coping with the challenges in high variety production by adopting process platforms. Accordingly, this paper proposes to model process platforms with focus on the application processes. In view of the significance of dynamic modelling and visualisation in shedding light on the logic of any processes, this study introduces a visual diagrammatic modelling language based on object-oriented (OO) techniques, named as OOVDML. With the graphical notations, uniquely shaped symbols, syntax and semantics, control mechanisms and arrangement rules, the OOVDML not only captures the logic of process platform's application but also provides a visualisation of their behaviours in a holistic view. Moreover, incorporating OO modelling allows readers to focus on their own interests. This study approaches to modelling process platform's application with respect to activities pertaining to customer order processing, engineering change control and production job planning. An industrial example of electronics products is also reported. The results of the case study not only show the suitability of the OOVDML but also shed light on the dynamic behaviours of process platforms.     

Modelling a maintenance management framework based on PAS 55 standard

This article shows the process of modelling a reference maintenance management framework (MMF) that represents the general requirements of the asset management specification PAS 55. The modelled MMF is expressed using the standardized and publicly available Business Process Modelling (BPM) languages UML 2.1 (Unified Modelling Language) and BPMN 1.0 (BPM Notation). The features of these notations allow to easily integrate the modelled processes into the general information system of an organization and to create a flexible structure that can be quickly and even automatically adapted to new necessities. This article presents a brief review about the usage of UML in maintenance projects, general characteristics of PAS 55, modelling concepts and their applications in the project of modelling the MMF. The arguments underlying the methodology and the choice of UML and BPMN are exposed. The general architecture of the suggested MMF is described and modelled through diagrams elucidating the general operation of PAS 55. From this development is appreciated the operation structure of a software tool that can incorporate MIMOSA standards and that can be made suitable for e‐maintenance functions, as an alternative to the commercial systems. Finally, some conclusions about the modelled framework are presented. Copyright © 2010 John Wiley & Sons, Ltd.     

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.     

WebML modelling in UML

In recent years, we have witnessed how the Web Engineering community has started using the standard unified modelling language (UML) notation, techniques and supporting tools for modelling Web systems, which has led to the adaptation to UML of several existing modelling languages, notations and development processes. This interest for being MOF and UML-compliant arises from the increasing need to interoperate with other notations and tools, and to exchange data and models, thus facilitating reuse. WebML, like any other domain-specific language, allows one to express in a precise and natural way the concepts and mechanisms of its domain of reference. However, it cannot fully interoperate with other notations, nor be integrated with other model-based tools. As a solution to these requirements, a UML 2.0 profile for WebML which allows WebML models to be used in conjunction with other notations and modelling tools has been described. The paper also evaluates UML 2.0 as a platform for Web modelling and identifies some key requirements for making this version of the standard more usable.     

Developing a practical framework for assessing ERP post-implementation success using fuzzy analytic network process

Implementing an enterprise resource planning system is a sophisticated, lengthy, and costly process which tends to face serious failure. Thus, it is essential to perform a success assessment at the post-implementation stage of an ERP project to evaluate how much the system has succeeded in achieving its predetermined objectives. This paper proposes a practical framework for assessing a firm's ERP post-implementation success utilising current models through a fuzzy analytic network process. The construct of ERP success is broken down into three main parts, including managerial success, organisational success, and individual success. Using this framework, the firm's ERP system success can be determined and the required improvement projects can be proposed to promote the success level. The proposed framework has been applied to a real international company, in the field of manufacturing and supplying turbines, to measure the firm's ERP post-implementation success. Finally, the advantages of the model are illustrated.     

Applying the TOC thinking process in manufacturing: A case study

A case study is presented to illustrate the application of the Theory of Constraints thinking process logic tools in a manufacturing environment. The study firm performs design activities related to meeting future product requirements while concurrently meeting existing production schedules for the current design of the product. Current approaches to managing the firm's limited productive capacity do not allow for both design and production activities to occur simultaneously while meeting the customer's current product delivery schedule. Thus, despite their desire to satisfy their customer's future design requirements, management uses the majority of its production capacity to meet its customer's current product delivery schedule. This case study demonstrates how a team of employees used thinking process logic diagrams to document reality, identify a core conflict and problem, develop proposed changes to address the core problem, and create several detailed action plans to implement changes within the study organization. Initially, scenarios associated with some undesirable effects are used to understand how prevailing policies and behaviours result in less than desired production line performance. Then, a current reality tree is constructed to link the core problem or system constraint with the previously identified undesirable effects. Next, two major injections are developed to address the core problem in managing the production line as logically documented in a future reality tree. Finally, three transition trees are presented to guide the implementation of change at the study organization.     

Assessing intermediate infrastructural manufacturing decisions that affect a firm's market performance

The purpose of this study is to develop a strategic operations management model that links intermediate infrastructural operations decisions and market performance given process choice as a structural constraint for manufacturing firms. The results underscore the effects of manufacturing control and staff skill and knowledge development on a firm's market performance. Several conclusions are drawn. First, manufacturing control, and staff skill and knowledge development has played significant roles in determining market performance. Second, either alone or in tandem with other independent variables, technology application dose not appear to be the most critical factor to affect a firm's market performance in today's Chinese business environment. Third, process type may not have a direct impact on market performance.     

Organizational development and time-based flexibility: An empirical analysis of AMT adoptions

It has been consistently reported that many firms that have adopted advanced manufacturing technology (AMT) are failing to exploit the true flexibility potential of these systems. Since a firm's ability to improve flexibility is thought to be reliant on the flexibility of its people, it is often suggested that inadequate emphasis on people-centred implementation activities such as worker development are major contributors to many of these failures. The purpose of this study is to determine if differences in the level of effort exerted on several organizational development activities have any impact on a firm's time-based flexibility ability to respond quickly to changes in customer needs. Our analysis indicates that firms which expend higher levels of effort on worker development and functional integration strategies will achieve higher levels of time-based flexibility.     

The Impact of Open Source Software Commercialization on Firm Value

Vendors of proprietary software products are increasingly moving to business models inspired by open source software (OSS). This study investigates sources of heterogeneity in value appropriation associated with commercializing OSS. Specifically, I suggest that the relationship between a firm's OSS releases and its value depends critically on its stocks of protection mechanisms for intellectual property rights, such as software patents and software trademarks. I find that while software patent stocks positively affect the relationship between a firm's OSS product portfolio and its value, software trademark stocks have a negative effect on this relationship.     

Supplier development or supplier switching?

We study a firm's cost-based sourcing decision of whether to invest in an incumbent supplier or switch to an alternative supplier in order to realise lower purchasing costs. In isolation, it can be shown that the development of an incumbent supplier (i.e., a cooperative investment) becomes more attractive, the higher the uncertainty about the price the buying firm can realise on the market and the incumbent supplier's cost. Likewise, switching to an alternative supplier becomes more attractive, the higher the expected value of and the uncertainty about the buying firm's market price. For comparing these two sourcing strategies simultaneously we provide a profit-maximising framework for the buying firm that shows that switching is less recommendable the higher the variance of the incumbent's cost and if the uncertain maximum demand is negatively correlated with the uncertain incumbent supplier's cost. Overall, our study substantially expands the frequently followed approach of basing supplier development versus supplier switching decisions merely on strategic and qualitative considerations.     

Incorporation of engineering knowledge into the modeling process: a local approach

Process modelling is the foundation of developing process controllers for monitoring and improving process/system health. Modelling process behaviours using a pure empirical approach might not be feasible due to limitation in collecting large amount of data. Engineering models provide valuable information about processes’ general behaviours but they might not capture distinct characteristics in the particular process studied. Many recent publications presented various ideas of using limited experimental data to adjust engineering models for making them suitable for certain applications. However, the focuses there are global adjustments, where modification of engineering models impacts the entire model-application region. In practice, some engineering models are only valid in a part of experimental data domain. Moreover, many discrepancies between engineering models and experimental data are in local regions. For example, in a chemical vapour deposition process, at high temperatures a process may be described by a diffusion limited model, while at low temperatures the process may be described by a reaction limited model. To address these problems, this article proposes two approaches for integrating engineering and data models: local model calibration and local model averaging. Through the local model calibration, the discrepancies between engineering’s first-principle models and experimental data are resolved locally based on experts’ feedbacks. To combine models adjusted locally in some regions and also models required little adjustments in other regions, a model averaging procedure based on local kernel weights is proposed. The effectiveness of the proposed method is demonstrated on simulated examples, and compared against a well-known existing global-adjustment method.     

Assessing the input effect on productive efficiency in production systems: the value of information technology capital

It is an imperative task for management to measure an organization's performance against its peers, competitors or itself. Among the performance measures frequently used, productive efficiency concerns the effective usage of input resources in producing output. Moreover, we are still unclear about how to identify the sources of such efficiencies so as to explain their causes. The issue becomes even more relevant and important but uncertain if the intended factor can also be treated as a non-traditional input in the production process. Treating information technology as a non-ordinary capital, this paper explores its effect on productive efficiency in a two-stage procedure. The first stage uses productive efficiency derived from parametric stochastic production frontiers models to measure the firm's performance, comparing the models with and without information technology investment as an independent input factor. The second stage then applies the non-parametric Wilcoxon signed-ranks method to test whether the information technology input has a positive impact on productive efficiency. The procedure is applied to a firm-level data set to corroborate the positive input effect of information technology on productive efficiency in the production system.     

Mathematical models in materials science

Abstract

Modelling has now become a routine part of materials science. It is appropriate therefore to assess some of the successes and failures of the method and to understand how and if modelling differs from ordinary quantitative science. The subject is now sufficiently mature to bear some constructive self-criticism and to temper exaggerated claims. The discussion here of modelling methods and outcomes is intended to be generic, although the examples used come from the author's experience of work on metals.     

Modelling the initial phase of an epidemic using incidence and infection network data: 2009 H1N1 pandemic in Israel as a case study

This paper presents new computational and modelling tools for studying the dynamics of an epidemic in its initial stages that use both available incidence time series and data describing the population''s infection network structure. The work is motivated by data collected at the beginning of the H1N1 pandemic outbreak in Israel in the summer of 2009. We formulated a new discrete-time stochastic epidemic SIR (susceptible-infected-recovered) model that explicitly takes into account the disease''s specific generation-time distribution and the intrinsic demographic stochasticity inherent to the infection process. Moreover, in contrast with many other modelling approaches, the model allows direct analytical derivation of estimates for the effective reproductive number (R_e) and of their credible intervals, by maximum likelihood and Bayesian methods. The basic model can be extended to include age–class structure, and a maximum likelihood methodology allows us to estimate the model''s next-generation matrix by combining two types of data: (i) the incidence series of each age group, and (ii) infection network data that provide partial information of ‘who-infected-who’. Unlike other approaches for estimating the next-generation matrix, the method developed here does not require making a priori assumptions about the structure of the next-generation matrix. We show, using a simulation study, that even a relatively small amount of information about the infection network greatly improves the accuracy of estimation of the next-generation matrix. The method is applied in practice to estimate the next-generation matrix from the Israeli H1N1 pandemic data. The tools developed here should be of practical importance for future investigations of epidemics during their initial stages. However, they require the availability of data which represent a random sample of the real epidemic process. We discuss the conditions under which reporting rates may or may not influence our estimated quantities and the effects of bias.     

Firms’ integrating efforts to mitigate the tradeoff between controllability and flexibility

We consider three manufacturing capabilities: controllability, flexibility, and integrating capability. Controllability is a firm's ability to control its process to enhance efficiency and accuracy and to better meet specifications. Flexibility is a firm's ability to cope with uncertainty and variation, both internal and external. Integrating capability is a firm's ability to integrate and coordinate diverse functions and parts of its supply chain, embodied in overall operations effectiveness and new product innovation. We put forth two hypotheses. First, there is an inherent tradeoff between controllability and flexibility. Second, a firm's integrating effort across its supply chain enables it to overcome such a tradeoff, making it possible to improve both controllability and flexibility simultaneously. Using data from 193 manufacturing companies, we test our hypotheses. It turns out that the relationship between controllability and flexibility is convex-shaped, indicating there are two distinct regions: one in which the relationship is negative and the other, positive. Further, the firms in the positive relationship region make significantly more effort to integrate, that is to say coordinate and communicate, across their supply chains, implying that as the firm strives to integrate its supply chain functions, it can mitigate the tradeoff between controllability and flexibility to a considerable extent.     

The development of a conceptual model regarding the role of social modelling in safety behaviour: an integrated literature review

Social modelling is a process where an individual observes a model's behaviour and its consequences, leading to a modification of the observer's old behaviours or the acquisition of new behaviours. Even though diverse fields, including transportation and aviation, have reliably found significant results pertaining to the influences of social modelling on behavioural outcomes, there is a lack of research pertaining to social modelling's influences specifically on safety behaviour. This review details the safety issues related to the mechanisms, influences and effects of social modelling as a way to examine the potential that social modelling has in affecting employees’ safety behaviour. The collected research materials aided in the construction of a preliminary conceptual model regarding the effects of social modelling on safety behaviour. Overall, the review provides safety and organisational researchers with information about a gap in the safety literature and a model that can lead to future research to fill that gap.     

Supply chain management practices as a mediator of the relationship between operations capability and firm performance

The current study uses mediated regression analysis and structural equation modelling to test the proposition that supply chain management practices mediate the relationship between operations capability and firm performance. Operations capability is defined in terms of a firm's new product design and development, total quality management and just-in-time capabilities. Results support the research model and also suggest the existence of a direct relationship between operations capability and performance.     

Structural and infrastructural practices as elements of content operations strategy. The effect on a firm's competitiveness

Some extant theoretical studies and different empirical results have demonstrated that a firm's behaviour explains several notable competitiveness microeconomic foundations, based on a wide bundle of elements. Firms can directly control most of these elements; in this paper, we will focus on those related to operations management. Therefore, products, processes, technology, equipments or quality control systems will centre our attention. These, and some additional elements, constitute decisions within the operations management area that must be included in the content of operations strategy. Operations strategy can be conceptualized as a set of decisions or practices with regard to structure and infrastructure variables. On the one hand, these strategic decisions influence a firm's abilities successfully to reach some competitive priorities such as cost, quality, delivery and flexibility, and, on the other hand, to obtain the expected performance. This research analyzes which are the main structural and infrastructural practices that constitute operations strategies in manufacturing companies, and investigates the effect of these decisions on some firm competitiveness indicators.     

A framework for measuring success of cellular manufacturing implementation

This paper analyses a part of the data collected in a survey of US firms that operate manufacturing cells. The paper identified two underlying dimensions or constructs that explain the relationships amongst the performance measures commonly used to assess the relative magnitude of success of cellular manufacturing (CM) implementation. These are: (1) delivery response (D R), and (2) quality-cost (QC). Scrap-rework and throughput time were identified as appropriate surrogate measures respectively for QC and D R, indicating that those two variables may suffice to monitor success of CM implementation. The firms report significantly greater improvements in D R variables than they do in QC. The paper also proposes a methodology to categorize relative success of CM implementation. Noting that no manager would volunteer to categorize his implementation efforts as a failure, the categorization scheme proposed can be utilized regardless of the firm's claims. Interpreting success within the framework of the proposed classification scheme, further analyses show that plants with a large number of product lines or operating a large number of cells tend to be more successful than others. However, the degree of success of CM implementation does not seem to be impacted by cell independence or whether the plant is unionized or not.