Equipment replacement decisions and lean manufacturing

Traditional manufacturing systems are built on the principle of economies of scale. Here, the large fixed costs of production are depreciation-intensive because of huge capital investments made in high-volume operations. These fixed costs are spread over large production batch sizes in an effort to minimize the total unit costs of owning and operating the manufacturing system. As an alternative to “batch-and-queue,” high-volume, and inflexible operations, the principles of the Toyota Production System (TPS) and lean manufacturing have been widely adopted in recent years in the US [1, 2, 3 and 4]. In this paper, we illustrate an equipment replacement decision problem within the context of lean manufacturing implementation. In particular, we demonstrate how the value stream mapping (VSM) suite of tools can be used to map the current state of a production line and design a desired future state. Further, we provide a roadmap for how VSM can provide necessary information for analysis of equipment replacement decision problems encountered in lean manufacturing implementation.     

What did you learn from practice today? Exploring experiences from a Danish R&D effort in digital construction

The Architecture-Engineering-Construction (AEC) industry has been slow in turning the potential of Information and Communication Technologies into greater efficiency and productivity. This is a phenomenon which can be observed in many countries, and in Denmark this issue has been recognized as a major problem for the further development of the AEC industry. The public-private and nationally funded R&D program ‘Digital Construction’ was initiated in 2003 to establish a common platform for exchanging digital information and stimulating digital integration in the Danish AEC industry. This paper reports on the lessons learned from developing strategies, demands and guidelines in the ‘Digital Construction’ program and from adapting one of its ‘digital foundations’, the ‘3D Working Method’, to the design process of the large-scale building project ‘The Icelandic National Concert and Conference Centre’. The explorations are based on a process evaluation of the R&D program and a qualitative case study of the building project. The paper reports on identified factors enabling or hindering the adaptation, as well as on the benefits and challenges experienced from using and exchanging 3D object models according to the ‘3D Working Method’. The paper concludes that the adaptation has been successful due to the initial ambitions of the project actors. Nevertheless, there are still many challenges to be overcome. The findings indicate that the introduction of the ‘3D Working Method’ to the real-life project depended on the success of balancing an array of the factors identified across the R&D program and the different levels within the building project. Three especially crucial balancing acts are explored; first, the power of the ‘implementer’ versus the expected risk and benefits of implementation, second, the strategies and guidelines within the program versus the resources for learning and the organizational traditions for using digital tools, and third, the level of ambition versus the skills of the users and the potential of the technology to address real-life practice. Mastering these balancing acts requires a broad understanding of both the project and its context. The findings from qualitative and holistic studies as presented in this paper are valuable for building such understanding, and for further learning and improvement regarding strategies for integrating ICT in architectural and engineering practice.     

Categorizing commercial products for customer oriented online retailing

Online retailing can offer several benefits. In order to realize these benefits, a commercial web site needs to ameliorate its deficiencies due to the absence of actual physical products. Although the use and popularity of the Internet continues to increase, it is still unclear how online retailers can establish effective online retailing strategies to capitalize on their benefits. For this clarification, this paper proposes a framework to categorize products according to consumers’ involvement and information quality fitness. Involvement refers to the degree of psychological identification or emotional ties consumers have with a particular product. Information quality fitness refers to the extent to which a product can fit with shopper’s requirements for online information. Thirty-six commercial products are empirically tested. It is found that products can be grouped into four categories such as ‘complex,’ ‘intelligent,’ ‘light,’ and ‘simple.’ This categorization can help understand product characteristics when they are sold via the Internet. Our finding implies that online retailers need to formulate their retailing strategies in view of these product categories.     

Towards a framework for energy-aware information systems in manufacturing

Environmental concerns, stricter legislation and inflated energy costs, together yield energy efficiency as an important pillar for virtually every industrial sector. Mindful of this challenge, ISs can act as enablers of energy-based management and intelligent decision support. Based on empirical evidence through two case studies combined with the design of a system prototype, this paper identifies those major functionalities that suffice to characterize an IS as ‘energy-aware’ in manufacturing. The functionalities are classified into two broad categories: (a) energy monitoring and (b) energy-aware analytics and are then combined into a high-level architecture. As a prerequisite for deploying such functionalities, this research presents also an approach integrating energy and operational information flows. Beyond that, the technologies that support the real-time and large-scale handling of energy data are provided. Our effort scales up to introduce a generic framework of a case-independent energy-aware IS.     

An intelligent method for selecting optimal materials and its application

Material selection is associated with all design and manufacturing problems. This paper presents an intelligent method to deal with the materials selection problems wherein the design configurations, working conditions, as well as the design-relevant information are not precisely known. The presented method is applied to select optimal materials for robotic components at an early stage of design. A computing tool is developed in order to implement the method. Unlike other materials selection methods, the presented method does not require derivation of material indices, extraction of “if … then …” rules, or cumbersome inference calculations. However, like material index based selection method, it uses widely available material property charts as material-relevant information. This way the method is made more user-friendly and realistic.     

Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems

A new efficient optimization method, called ‘Teaching–Learning-Based Optimization (TLBO)’, is proposed in this paper for the optimization of mechanical design problems. This method works on the effect of influence of a teacher on learners. Like other nature-inspired algorithms, TLBO is also a population-based method and uses a population of solutions to proceed to the global solution. The population is considered as a group of learners or a class of learners. The process of TLBO is divided into two parts: the first part consists of the ‘Teacher Phase’ and the second part consists of the ‘Learner Phase’. ‘Teacher Phase’ means learning from the teacher and ‘Learner Phase’ means learning by the interaction between learners. The basic philosophy of the TLBO method is explained in detail. To check the effectiveness of the method it is tested on five different constrained benchmark test functions with different characteristics, four different benchmark mechanical design problems and six mechanical design optimization problems which have real world applications. The effectiveness of the TLBO method is compared with the other population-based optimization algorithms based on the best solution, average solution, convergence rate and computational effort. Results show that TLBO is more effective and efficient than the other optimization methods for the mechanical design optimization problems considered. This novel optimization method can be easily extended to other engineering design optimization problems.     

Developing a quantitative intelligent system for implementing concurrent engineering design

This research focuses on the development of a quantitative intelligent system for implementing concurrent engineering design. The paper first discusses the task of concurrent engineering design and the basic requirements for conducting integrated concurrent engineering design. The proposed quantitative intelligent system approach combines qualitative reasoning, based upon design and manufacturing knowledge, and quantitative evaluation and optimization, conducted using design information and manufacturing data generated in the knowledge-based reasoning. The method allows considerations on non-operating principle aspects of a product to be incorporated into the design phase, such as manufacturing, maintenance, service, recycle, etc., with an emphasis on production costs. The proposed method serves as a convenient software tool for gathering information required in the concurrent engineering design process and integrates tasks from different parts of the product development life cycle, particularly function design, manufacturability analysis and production cost estimation. A prototype software system is developed based upon this method using Smalltalk-80. In the prototype system, concurrent engineering design is carried out by: (1) describing and representing design requirements; (2) generating feasible design candidates and evaluating their design functions; (3) representing design geometry; (4) finding the associated production processes and predicting the production costs of each feasible design; and (5) identifying the costeffective design that satisfies given design requirements and requires minimum production costs.     

On Resource Arc for Petri Net Modelling of Complex Resource Sharing System

PFS-R – Production Flow Schema with Resources – is a novel graphical representation for complex resource sharing discrete production systems proposed in this paper. The PFS-R is an augmented version of the PFS (Production Flow Schema, previously proposed by the authors) which includes correspondences of system resources at each production step. The PFS-R is able to model system structures as well as system behaviours in a more simplified and transparent manner than ordinary Petri net representations. That is, the PFS-R solves an important drawback when actually adopting Petri nets as a design technique for intelligent manufacturing systems. First, the paper introduces the basic elements of PFS-R, and the equivalent transformations of PFS-R model into hybrid nets and Petri nets, taking into account the net conservativeness. Next, examples of discrete production systems to illustrate the effectiveness of PFS-R are presented. In addition, it is shown, using an example, that the correspondence between resources and production steps in the process flow has a tree structure, which is an effective way to evaluate whether or not the objects designed have a well-defined structure.     

Web-based quiz-game-like formative assessment: Development and evaluation

This research aims to develop a multiple-choice Web-based quiz-game-like formative assessment system, named GAM-WATA. The unique design of ‘Ask-Hint Strategy’ turns the Web-based formative assessment into an online quiz game. ‘Ask-Hint Strategy’ is composed of ‘Prune Strategy’ and ‘Call-in Strategy’. ‘Prune Strategy’ removes one incorrect option and turns the original 4-option item into a 3-option one. ‘Call-in Strategy’ provides the rate at which other test takers choose each option when answering a question. This research also compares the effectiveness of three different types of formative assessment in an e-Learning environment: paper-and-pencil test (PPT), normal Web-based test (N-WBT) and GAM-WATA. In total, 165 fifth grade elementary students (from six classes) in central Taiwan participated in this research. The six classes of students were then divided into three groups and each group was randomly assigned one type of formative assessment. Overall results indicate that different types of formative assessment have significant impacts on e-Learning effectiveness and that the e-Learning effectiveness of the students in the GAM-WATA group appears to be better. Students in the GAM-WATA group more actively participate in Web-based formative assessment to do self-assessment than students in the N-WBT group. The effectiveness of formative assessment will not be significantly improved only by replacing the paper-and-pencil test with Web-based test. The strategies included in GAM-WATA are recommended to be taken into consideration when researchers design Web-based formative assessment systems in the future.     

Drawing curves onto a cloud of points for point-based modelling

Point-based geometric models are gaining popularity in both the computer graphics and CAD fields. A related design/modelling problem is the focus of the reported research: drawing curves onto digital surfaces represented by clouds of points. The problem is analyzed and solved, and a set of ‘design tools’ are proposed which allow the user/designer to efficiently perform ‘product development’ (alternative name: ‘detail design’) tasks which require efficient processing of a ‘digital surface’. The primary tool is a robust and efficient point projection algorithm combined with a smoothing technique for producing smooth ‘digital curves’ lying onto the cloud surface. The new design tools are tested on a real-life industrial example with very satisfactory results, which are thoroughly presented in the paper.     

Beating the baseline prediction in food sales: How intelligent an intelligent predictor is?

Sales prediction is an essential part of stock planning for the wholesales and retail business. It is a complex task because of the large number of factors affecting the demand. Designing an intelligent predictor that would beat a simple moving average baseline across a number of products appears to be a non-trivial task. We present an intelligent two level sales prediction approach that switches the predictors depending on the properties of the historical sales. First, we learn how to categorize the sales time series into ‘predictable’ and ‘random’ based on structural, shape and relational features related to the products and the environment using meta learning approach. We introduce a set of novel meta features to capture behavior, shape and relational properties of the sales time series. Next, for the products identified as ‘predictable’ we apply an intelligent base predictor, while for ‘random’ we use a moving average. Using the real data from a food wholesales company we show how the prediction accuracy can be improved using this strategy, as compared to the baseline predictor as well as an ensemble of predictors. In our study we also show that by applying an intelligent predictor for the most ‘predictable’ products we can control the risk of performing worse than the baseline.     

Integrating ergonomics into production system development - The Volvo Powertrain case

Understanding the barriers and assists to integrating ergonomics into production system design remains a research issue. An action research case study at Volvo Powertrain/Sweden was conducted. Researchers worked collaboratively with the firm in efforts to improve the company's ability to handle ergonomics in their daily work of improving and developing production systems. Researchers observed and reflected collectively on the change process using field notes and recordings to support their observations.Observed integration barriers included both individual level issues like life events, and organisational aspects such as communication barriers between groups or assignment of tasks to people not involved in decision-making. Observed assists included the ‘political reflective navigation’ (c.f. Broberg, O., Hermund, I., 2004. The OHS consultant as a ‘political reflective navigator’ in technological change processes. International Journal of Industrial Ergonomics 33 (4), 315-326) by the project owner to find new ways to overcome barriers and anchor ergonomics into the organisation. While special ‘ergonomics’ groups did not survive long, progress was observed in including ergonomics in regular design groups. A cross-functional workshop that fostered discussion across organisational boundaries helped shift focus from retrofitting systems to future production systems and improve engagement of engineering teams. Progress was marked by both success and setbacks and full integration appears to require more than 2 years time. It is concluded that support by senior managers should include succession planning for personnel that are key to the change effort.     

CAD tools for aesthetic engineering

The role of computers and of computer-aided design tools for the creation of geometrical shapes that will be judged primarily by aesthetic considerations is reviewed. Examples are the procedural generation of abstract geometrical sculpture or the shape optimization of constrained curves and surfaces with some global ‘cost’ functional. Different possibilities for such ‘beauty functionals’ are discussed. Moreover, rapid prototyping tools based on layered manufacturing now add a new dimension to the visualization of emerging designs. Finally, true interactivity of the CAD tools allows a more effective exploration of larger parts of the design space and can thereby result in an actual amplification of the creative process.     

Modular production systems: a new manufacturing paradigm

It is well recognized that manufacturers of consumer goods throughout the world are facing major new demands, including shorter product life-cycles and increasing competition. In response, companies are restructuring and moving away from traditional process-centred work practices in favour of concurrent engineering methods. In particular, design for manufacture has gained widespread recognition as a means of reducing production costs and lead times. However, optimal design for manufacture is difficult to achieve using current-day work organization and business structures. An underlying problem is the lack of a scientific framework for production. To address this need, this paper proposes a radical and far-reaching new manufacturing paradigm based upon on building production systems from standardized modular machines. The manufacturing concept, termed modular production systems (MPS), is aimed specifically at hard low- to medium-technology consumer products, as typified by goods such as childrens toys and kitchen appliances. The rationale for MPS as a means of enabling concurrent product and production system design is put forward, and the long-term implications and work required to establish the concept are discussed.     

From screening to quantitative sensitivity analysis. A unified approach

The present work is a sequel to a recent one published on this journal where the superiority of ‘radial design’ to compute the ‘total sensitivity index’ was ascertained. Both concepts belong to sensitivity analysis of model output. A radial design is the one whereby starting from a random point in the hyperspace of the input factors one step in turn is taken for each factor. The procedure is iterated a number of times with a different starting random point as to collect a sample of elementary shifts for each factor. The total sensitivity index is a powerful sensitivity measure which can be estimated based on such a sample. Given the similarity between the total sensitivity index and a screening test known as method of the elementary effects (or method of Morris), we test the radial design on this method. Both methods are best practices: the total sensitivity index in the class of the quantitative measures and the elementary effects in that of the screening methods. We find that the radial design is indeed superior even for the computation of the elementary effects method. This opens the door to a sensitivity analysis strategy whereby the analyst can start with a small number of points (screening-wise) and then – depending on the results – possibly increase the numeral of points up to compute a fully quantitative measure. Also of interest to practitioners is that a radial design is nothing else than an iterated ‘One factor At a Time’ (OAT) approach. OAT is a radial design of size one. While OAT is not a good practice, modelers in all domains keep using it for sensitivity analysis for reasons discussed elsewhere (Saltelli and Annoni, 2010) [23]. With the present approach modelers are offered a straightforward and economic upgrade of their OAT which maintain OAT's appeal of having just one factor moved at each step.     

Qualitative reachability in stochastic BPA games

We consider a class of infinite-state stochastic games generated by stateless pushdown automata (or, equivalently, 1-exit recursive state machines), where the winning objective is specified by a regular set of target configurations and a qualitative probability constraint ‘>0’ or ‘=1’. The goal of one player is to maximize the probability of reaching the target set so that the constraint is satisfied, while the other player aims at the opposite. We show that the winner in such games can be determined in P for the ‘>0’ constraint, and in NP∩co-NP for the ‘=1’ constraint. Further, we prove that the winning regions for both players are regular, and we design algorithms which compute the associated finite-state automata. Finally, we show that winning strategies can be synthesized effectively.     

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.     

Design with part behaviors: behavior model, representation and applications

A part is primarily characterized by its ‘function(s)’. The function of the part is achieved through its ‘interactions’ with other parts in an assembly under a set of operating conditions. These ‘interactions’ constitute the ‘behavior’ of the part. The ‘part behavior’ is achieved through a set of spatial and design functional relationships between the interacting surfaces of the parts. The set of spatial and design functional relationships for a part constitutes the Part Function Model (PFM) of that part. In this paper, the nature and role of part ‘functions’ and ‘behaviors’ have been studied in the context of a product design system. The paper addresses the following issues: (i) relationship between function, behavior, and geometry of a part; (ii) importance of ‘part behavior’ over ‘part function’, and development of a ‘part behavior’ model; (iii) methodology for transforming the part behaviors into the PFM model of the part; (iv) product model framework for storing the PFM model information with an Object Oriented Programming (OOP) based CAD system (Concentra's Concept Modeller); (v) importance of the PFM model within the product development process; and (vi) application of the PFM model for generating various product specifications of the part. The prototype implementation of a Functional Design System for transforming part behaviors into different types of part specifications has also been presented in this paper.     

Discrete event-driven model predictive control for real-time work-in-process optimization in serial production systems

Advanced technologies (e.g., distributed sensors, RFID, and auto-identification) can gather processing information (e.g., system status, uncertain machine breakdown, and uncertain job demand) accurately and in real-time. By combining this transparent, detailed, and real-time production information with production system physical properties, an intelligent event-driven feedback control can be designed to reschedule the release plan of jobs in real-time without work-in-process (WIP) explosion. This controller should obtain the operational benefits of pull (e.g., Toyota’s Kanban system) and still develop a coherent planning structure (e.g., MRPII). This paper focuses on this purpose by constructing a discrete event-driven model predictive control (e-MPC) for real-time WIP (r-WIP) optimization. The discrete e-MPC addresses three key modelling problems of serial production systems: (1) establish a max-plus linear model to describe dynamic transition behaviors of serial production systems, (2) formulate a model-based event-driven production loss identification method to provide feedback signals for r-WIP optimization, and (3) design a discrete e-MPC to generate the optimal job release plan. Based on a case from an industrial sewing machine production plant, the advantages of the discrete e-MPC are compared with the other two r-WIP control strategies: Kanban and MRPII. The results show that the discrete e-MPC can rapidly and cost-effectively reconfigure production logic. It can decrease the r-WIP without deteriorating system throughput. The proposed e-MPC utilizes the available transparent sensor data to facilitate real-time production decisions. The effort is a step forward in smart manufacturing to achieve improved system responsiveness and efficiency.