The Fabricare system: a multi-agent-based scheduling prototype

Several trends in society in general, and manufacturing in particular, have changed the way business was made in the last decades of the 20th century, setting new requirements for companies and individuals. The research question being addressed in this paper is concerned with the ability to build computer-supported manufacturing systems able to cope with current and future requirements. For this matter, a hypothesis based on the holonic and multi-agent paradigms is proposed. The paper describes a holonic architecture for manufacturing enterprises and a prototype system (named Fabricare) for manufacturing orders scheduling based on that architecture. A negotiation mechanism called ‘contract net with constraint propagation protocol’ was developed for regulating the interaction between holons in the system. This protocol also implements a negotiation-driven scheduling procedure.     

Experimental push/pull production planning and control system

We introduce an experimental push/ pull production planning and control software system which is designed as an alternative to a MRP-II system for mass manufacturing enterprises in China. It has the following distinguishing features: (1) putting the philosophy of JIT into the master production scheduling of MRP-II via the earliness/ tardiness production planning method; (2) controlling material input by push and processing/ assembly by pull; and (3) adjusting the parameters of the production line by the‘ suggestion for improvement of production line’ module. Simulation results have shown that the proposed system can achieve better planning and control performance than existing systems.     

Agent-based interbay system control for a single-loop semiconductor manufacturing fab

This study investigates agent-based interbay control of a wafer fabrication facility with a single-loop track. Doing so will simultaneously resolve the production scheduling and vehicle dispatching problems for an interbay over-hoist-transportation system which is commonly employed in the semiconductor manufacturing industry. Two issues are focused on in this study: (i) To design appropriate agent-based control architecture for an interbay system and (ii) to develop a coordination mechanism for the autonomous agents in the interbay system, so that wafer manufacturing tasks can be accomplished efficiently. In this study, we construct a distributed interbay system architecture, in which wafer cassettes, vehicles, and manufacturing cells with stockers are modelled as independent and autonomous agents. This study develops an agent coordination mechanism that is based on a vehicle-initiated contract net protocol. Three types of bidding strategies are proposed and empirically examined via simulation. The performances of the proposed agent-based control mechanism, in terms of cassette sojourn time and throughput, are observed and our experiments have shown promising results.     

European high technology manufacturing: Choices on the path to manufacturing excellence

The author is concerned to point out that advanced manufacturing technologies have their main impact on ‘manufacturing deliverables’, particularly quality, delivery and cost. It is these deliverables that interest companies in their attempts to compete globally by using high technology strategies.The technologies themselves - computer aided design, computer numerical control, or optimised production technology, for instance, can be categorised into ‘high-tech’ or ‘lo-tech’. But the division is somewhat artificial, and the way forward may be pragmatic.     

Managing AMI in a Just-In-Time Environment in the UK and Japan

In recent years many commentators have addressed the ‘crisis’ in manufacturing industry (Gerwin, 1982; Drucker, 1988, 1990; Hayes and Jaikumar, 1988). Some have offered cross-national comparisons on Japanese and Western management methods and techniques (Kharbanda and Stallworthy, 1991; Oliver and Wilkinson, 1987; Pascale and Athos, 1981) whilst others have concentrated on improving performance in specific fields such as management accounting (Kaplan, 1984; Cooper, 1991) or manufacturing management (Schonberger, 1982; Halt, 1983). Empirical research into managing AMT in Japan and the UK (Currie 1991a) considers some of the broader managerial issues in manufacturing. Cultural differences are common in the areas of investment appraisal, post-auditing of AMT and preventive maintenance policy. For example, in Japan JIT is perceived ‘holistically’ incorporating production management, total quality assurance (TQA) and total preventive maintenance (TPM). This is contrary to the UK in that many large manufacturing companies fail to include TPM in their manufacturing strategies (Currie and Seddon, 1991). There are few management information systems (MIS) which provide an understanding of machine performance using both non-financial and financial information. Focusing on maintenance as a central theme, the paper discusses the development of the Failure And Scheduled Maintenance Analysis (FASMA) system, which offers a practical solution to the problem of collecting and manipulating manufacturing data on the shopfloor (Seddon, 1991a). Essentially, FASMA attempts to interface both the manufacturing and management accounting functions by translating machine performance data into valuable information from which preventive maintenance policy may be improved. Using FASMA to measure machine performance at a major UK automotive manufacturer, machine down-time has averaged 61% each month over a 3-year period. By manipulating this data, performance measurement information may be utilized by management accountants. FASMA thus develops a link between manufacturing and management accounting by providing data on machine performance which can be used for cost analysis within a manufacturing environment. The paper concludes by arguing that manufacturing strategies can only be developed using appropriate management information systems (MIS) designed to enhance functional integration. This will enable a better understanding of how the ‘manufacturing jigsaw’ fits together.     

A closed loop automatic scheduling system (CLASS)

Abstract

CLASS is a production scheduling system, that is designed to function in either a stand-alone manner, or in conjunction with an MRP system. MRP systems innately do not have 'closed loop’ capability in the sense of being able to produce master schedules and order releases that are consistent and that respect capacity constraints. True closed loop performance requires detailed scheduling. In addition to interfacing with MRP systems, CLASS is designed to produce schedules that can be used in conventional shops or can be downloaded to automated facilities. The design goals for the system, its internal architecture, and its role in manufacturing control systems are described. The modelling and decision capabilities     

Labour Market Flexibility,Human Resource Management and Corporate Performance

Labour market flexibility is often portrayed as a key to the competitive success of the UK and US economies. We surveyed several hundred firms in the UK, and using the resulting data (on over 200 manufacturing firms) this paper investigates the relationships between firms’ use of flexible work practices, human resource systems and industrial relations on the one hand, and corporate performance on the other hand. The results suggest that ‘low‐road’ practices – short‐term contracts, a lack of employer commitment to job security, low levels of training and low levels of human resource sophistication – are negatively correlated with corporate performance. In contrast, it is found that ‘high‐road’ work practices –‘high commitment’ organizations or ‘transformed’ workplaces – are positively correlated with good corporate performance. It is also found that human resource management practices are more likely to contribute to competitive success where they are introduced as a comprehensive package, or ‘bundle’ of practices. Significant interaction effects between human resource systems, trade unions and flexible work practices add further support to the bundling hypothesis.     

Judicious order acceptance and order release in make-to-order manufacturing systems

This paper explores a two-stage input control system for fixed capacity make-to-order manufacturing systems (with heavy job tardiness penalties), that selectively accepts incoming orders and holds the accepted ones in a pre-shop queue prior to releasing them to the shop floor. Single-stage input control systems that only allow orders to be delayed in a pre-shop queue (i.e. they do not allow some orders to be rejected) have been previously investigated and found to negatively impact overall due-date performance. The hypothesis motivating this research is that judiciously rejecting a subset of incoming orders can prevent the order release queue from being overloaded when a surge of demand occurs. The input control system is evaluated via experiments using a discrete-event simulation model of a fixed capacity manufacturing system. The experiments reported here suggest that holding orders in the pre-shop queue does not improve due date performance, and that judiciously rejecting orders on its own is a viable alternative mechanism of input control that can deliver improved performance.     

Simulation-based performance assessment of master planning approaches in semiconductor manufacturing

Semiconductor manufacturing is confronted with a large number of products whose mix is changing over time, heterogeneous fabrication processes, re-entrant flows of material, and different sources of environmental and system uncertainty. In this context, the mid-term production planning approach, i.e., master planning, typically does not capture the entire complexity of the shop-floor. It deals with an aggregated representation of the production system. There is a need for evaluating the planning algorithm in use while taking the execution level into account. Therefore, we introduce in this paper a simulation-based framework that allows for modeling the behavior of the market demand and the production system. An appropriate performance assessment methodology is proposed. The performance of two heuristic approaches for master planning in semiconductor manufacturing, a genetic algorithm and a rule-based assignment procedure, is evaluated within a rolling horizon setting while considering demand and execution uncertainty. A reduced discrete-event simulation model is used to mimic a one-stage network of wafer fabrication facilities. The results of simulation experiments are discussed.     

A taxonomy of international manufacturing networks

Abstract

Manufacturing firms with multiple product groups do not need to involve all factories in the production of all product groups. Some factories may specialize on a small set of products, while others participate in the manufacturing of a broader set of products. However, current theories on international manufacturing networks do not explain in detail how organizations design international manufacturing networks for different products or product groups involving different sets of factories. This research investigates 20 product group networks at five global manufacturing firms. We distinguish between three types of factories: component manufacturing factories, assembly factories, and integrated factories (having both component manufacturing and assembly). Furthermore, we identify four network types: linear, divergent, convergent, and mixed structures. These four types exhibit distinctly different characteristics in terms of key characteristics, factory roles, product types, process types, market types, sourcing, and key managerial challenges. Most networks are relatively small – on an average consisting of four factories and some contain a number of subnetworks that are self-sufficient in terms of material flow and serve separate market regions. We identify two new types of factory roles related to component manufacturing competences, which we call ‘strategic feeder’ and ‘full lead’.     

An exploration of ‘sticky’ inventory management in the manufacturing industry

Traditional models examining relationships between firm resources and revenues assume that the many expenses and asset holdings change in proportion to changes in demand. However, research has found that for many costs and assets assumed to be variable, the magnitude of a change in a cost or asset in proportion to a change in revenue is smaller during periods when revenue decreases compared to the change in the cost or asset when revenue increases. Costs and assets which behave in this manner have been denoted as ‘sticky’ costs or assets. This study examines if inventory in the manufacturing industry is managed in a ‘sticky’ manner and what implications inventory stickiness has on firm performance. Utilising firm panel data over a 25-year time window we find that inventory stickiness does exist amongst manufacturers and that it has negative implications for firm performance.     

High value manufacturing (HVM) in the UK: case studies and focus group insights

This paper studies the internal mechanisms that allow organisations to become high value manufacturing (HVM). Using a qualitative methodology, three UK manufacturing companies formed in-depth case studies with semi-structured interviews, observations and historical data. The HVM value matrix of Martinez and co-workers is used to categorise each organisation’s value proposition. Wider benchmarking of the three organisations was carried out against a focus group with an additional seven manufacturing organisations. Thus, data from 10 manufacturing organisations are included in this research. The cases follow the ‘customer intimacy’ HVM discipline. The business processes supporting these value propositions were identified. Interestingly, each organisation’s desired value proposition differs from their current one. ‘Technological integrators’ predominantly rely on new product development (NPD) and Strategy processes, whereas ‘Socialisors’ rely predominantly on Strategy and Customer Relationship processes. Companies can use the findings to better understand their current HVM value proposition and, where necessary, plan their transition to a future desired HVM value proposition.     

Implementation of holonic scheduling and control in flow-line manufacturing systems: die-casting case study

The success of a flow-line manufacturing system depends on effective production scheduling and control. However, it has been found that current flow-line manufacturing scheduling and control algorithms lack the flexibility to handle interruptions or resource breakdowns; hence, system performance drops automatically and rapidly when interruptions occur. The objective of this research is to investigate if the performance of a flow-line manufacturing system can be improved by integrating agent-based, holonic scheduling and production control. A holonic manufacturing scheduling model has been developed and implemented into a die-casting manufacturing flow line throughout a simulation model. The analysis takes into account the comparisons of overall performances of the system models with the holonic scheduling and conventional scheduling approaches. Simulation results indicate that the holonic manufacturing scheduling and control can significantly increase the uptime efficiency and the production rate of the flow-line manufacturing system.     

Defining and assessing industry 4.0 maturity levels – case of the defence sector

Abstract

Firms do not currently fully appreciate the complex characteristics of Industry 4.0 and as a result are uncertain about what it represents for them. In this study, an assessment model is developed to measure the level of implementation of Industry 4.0 technologies, around three dimensions: ‘Factory of the Future’, ‘People and Culture’, and ‘Strategy’. The ‘Factory of the Future’ is the main dimension and is composed of eight attributes: Additive Manufacturing, Cloud, Manufacturing Execution System, Internet of Things and Cyber Physical Systems, Big Data, Sensors, e-Value Chains, and Autonomous Robots. The study uses a defence manufacturing firm to develop, test and validate the model and report on 12 partners. We concluded that the focal firm has an Industry 4.0 maturity level of 59.35, above the sector average of 55.58. This research contributes by empirically developing a model and providing an analysis of major firms in the Defence supply network.     

A practical approach to achieving Agility–a theory of constraints perspective

This article documents an action research (AR) project aimed at identifying the practical steps needed to become an agile manufacturer through a combination of the theory of constraints (TOC) and resource- based view (RBV) approaches in a small to medium enterprise (SME) in the Australian manufacturing sector. To date, lean production has been highlighted as a possible catalyst for creating an agile manufacturer, despite the evidence suggesting that lean manufacturing lacks the responsiveness and adaptability to effectively handle a rapidly changing market place and only works well in a stable environment. A more flexible system of production is required to fully encompass the agile characteristics needed to attain a competitive advantage. This research provides empirical evidence that the TOC perspective can be used as a practical approach for becoming an agile manufacturer. The study provides a workable approach for small firms to achieve ‘Agility’ in practice.     

A decision support system for modelling and implementing the supply network configuration and operations scheduling problem in the machine tool industry

This paper presents a decision support system to simultaneously solve the supply network configuration problem and the operations scheduling problem for the machine tool industry. A novel database structure, which is able to consider alternative operations and alternative bills of material, has been used. An algorithm for complete enumeration to determine all the feasible solutions using stroke graphs is introduced. A multiagent-based simulator evaluates the different key performance indicators that the supply network deals with for each alternative solution (e.g. workload, profits, delivery times, etc.) to determine that ‘satisficed’ by the collaborative decision-making among its members. A case study based on a Spanish company that assembles highly customised machines and tools in several European plants is considered. From the experiments results based on data linked to this industry, it will be demonstrated that the tool is potentially useful for stakeholders and for the central decision-maker to make decisions collaboratively in a multisite context case.     

Integrated Ant Colony and Tabu Search approach for time dependent vehicle routing problems with simultaneous pickup and delivery

Today manufacturers have become much more concerned with the coordination of both manufacturing (of new products) and recycling (of reusable resources) operations. This requires simultaneous scheduling of both forward and reverse flows of goods over a supply chain network. This paper studies time dependent vehicle routing problems with simultaneous pickup and delivery (TD-VRPSPD). We formulate this problem as a mixed integer programming model, where the time step function is used to calculate the travel time. To efficiently solve this complex problem, we develop a hybrid algorithm that integrates both Ant Colony System (ACS) and Tabu Search (TS) algorithms. Our algorithm uses the pheromones, travel time and vehicle residual loading capacity as a factor structure according to the characteristics of TD-VRPSPD. In our computational experiments, 56 groups of benchmark instances are used to evaluate the performance of our hybrid algorithm. In addition, we compare the performance of our hybrid algorithm with those of individual ACS and TS algorithms. The computational results suggest that our hybrid algorithm outperform stand-alone ACS and the TS algorithms.     

Strategic Influences of Technological Innovation in Greece

This exploratory paper analyses the ‘importance’ and ‘awareness’ of a set of established ‘strategic’ influences of technological innovation in the context of a European newly‐industrialized country. The author interviewed 105 Greek manufacturing firms (mainly SMEs) and measured their perceived innovation rate as well as 17 ‘strategic’ factors regarding top‐management practices and characteristics. Using correlation and regression analysis the initial group of factors was reduced to a subset of five ‘major importance’ influences of innovation, namely: incorporation of technology plans in the business strategy, managerial attitude towards risk, perceived intensity of competition and rate of change of customer needs, and finally status of the CEO (owner‐CEOs were associated with higher innovation rate than appointed CEOs). The ‘statistical’ results are exploratory and have to be treated with caution, as they are highly dependent on the accuracy of the respondents' perception of their company's innovation rate and top‐management practices and characteristics. The ‘statistical’ results were then compared with the managers' perception on the important factors determining innovation (also measured during the interviews). Overall the perceptual analysis confirmed the significance of the statistically important variables, with the exception of a disagreement in the direction of association between the status of the CEO and the rate of innovation. In general, top‐management characteristics proved more important ‘strategic’ influences of innovation for the Greek SMEs than corporate practices. The study also indicated that the important influences of innovation were generally scarce in the Greek institutional context. The highly innovative companies were the ones to overcome country‐specific innovation barriers such as the low supply of technology, the low level of competition and the risk‐averse national culture.     

Fuzzy Overall Equipment Effectiveness (FOEE): capturing performance fluctuations through LR Fuzzy numbers

The paper focuses on the Overall Equipment Effectiveness (OEE), a performance indicator that is extensively used in the industry. The aim is to extend the capabilities of the OEE, so as to capture the day-to-day fluctuations to which manufacturing performances are subjected. To this aim, manufacturing losses are decomposed into elementary causes and modelled as LR fuzzy numbers. Next, in order to compute the Fuzzy Overall Equipment Effectiveness (FOEE), single losses are aggregated using the ‘fuzzy transformation model’. This approach limits the fuzzy overestimation phenomenon and assures both results’ accuracy and robustness. An industrial application, part of a lean project carried on by an important Italian manufacturing firm, is finally presented. Results are encouraging, since the FOEE made it possible to trace back the share of the overall fluctuations that is ascribable to each cause of loss. In this way, it provided the basis for setting improvement priorities and directed the lean team toward the selection of appropriate corrective actions.     

A modularised typology for flow design based on decoupling points – a holistic view on process industries and discrete manufacturing industries

Management of production activities covers a wide range of decisions. In this paper, a modularised approach is suggested that, through configuration, generates a case-specific flow design. The approach is based on identification of decision categories that are generic and fundamental in the flow design, covering both discrete manufacturing industries and process industries. Each decision category identifies a unique property of the flow which changes at a particular point: this is termed a ‘decoupling point’. A three-dimensional modularised typology is developed by combining three different decision categories. Cases from the steel industry and the tooling industry are used to illustrate how the typology can be applied. The modularised approach provides a typology for the application of both qualitative and quantitative methods for flow management, including planning, control and performance management.