Cost performance dynamics in lean production leveling

Balancing of production systems is one of the main lean manufacturing principles as it reduces in-process storage and related forms of waste. A dynamic systems approach is proposed to investigate challenges of implementing production leveling and associated costs. A lean cell producing at takt time is modeled using system dynamics. The model captures various lean tools influencing production leveling and their implications. Comparative cost analysis between various leveling implementation policies for stochastic demand with multiple products is conducted. Results showed that determining the most feasible leveling policy is highly dictated by both the cost and limitations of capacity scalability. In addition, delivery sequence plans of different products/parts needed to achieve mix leveling and lot sizes affect the feasible production leveling policy while implementing lean principles. The developed model and insights gained from the results can help lean manufacturing practitioners to better decide when and how to implement production leveling as well as determine both production lots sizes and sequence. They also emphasize the importance of cost analysis as assisting decision support tool in the trade-off required between the benefits of different levels of lean policies and their associated cost.     

Integrated maintenance and operations decision making with imperfect degradation state observations

In highly flexible and integrated manufacturing systems, such as semiconductor fabs, strong interactions between the equipment condition, operations executed on the various machines and the outgoing product quality necessitate integrated decision making in the domains of maintenance scheduling and production operations. Furthermore, in highly complex manufacturing equipment, the underlying condition is not directly observable and can only be inferred probabilistically from the available sensor readings. In order to deal with interactions between maintenance and production operations in Flexible Manufacturing Systems (FMSs) in which equipment conditions are not perfectly observable, we propose in this paper a decision-making method based on a Partially Observable Markov Decision Processes (POMDP's), yielding an integrated policy in the realms of maintenance scheduling and production sequencing. Optimization was pursued using a metaheuristic method that used the results of discrete-event simulations of the underlying manufacturing system. The new approach is demonstrated in simulations of a generic semiconductor manufacturing cluster tool. The results showed that, regardless of uncertainties in the knowledge of actual equipment conditions, jointly making maintenance and production sequencing decisions consistently outperforms the current practice of making these decisions separately.     

Lean production system design for fishing net manufacturing using lean principles and simulation optimization

Value stream mapping (VSM) is a useful tool for describing the manufacturing state, especially for distinguishing between those activities that add value and those that do not. It can help in eliminating non-value activities and reducing the work in process (WIP) and thereby increase the service level. This research follows the guidelines for designing future state VSM. These guidelines consist of five factors which can be changed simply, without any investment. These five factors are (1) production unit; (2) pacemaker process; (3) number of batches; (4) production sequence; and (5) supermarket size. The five factors are applied to a fishing net manufacturing system. Using experimental design and a simulation optimizing tool, the five factors are optimized. The results show that the future state maps can increase service level and reduce WIP by at least 29.41% and 33.92% respectively. For the present study, the lean principles are innovatively adopted in solving a fishing net manufacturing system which is not a well-addressed problem in literature. In light of the promising empirical results, the proposed methodologies are also readily applicable to similar industries.     

Criteria for selecting control systems in flexible manufacturing

Industry in Europe has been undergoing major structural changes during the last twenty years or so. Against the background of high demand for consumer and capital goods with corresponding, mostly fixed production capacities, it was necessary to build flexible and, at the same time, efficient production plants in order to cope with the increasing variety of products and shorter innovation cycles.Flexible manufacturing is inconceivable without information technology. Thus, the word “information” has rightly taken its place in the list of primary factors associated with modern production technology. The “gating” of data into production planning and quality assurance, combined with concepts of logistics and control, keeps the flow of materials on the move and helps to shorten lead times.The organization of production and the plant equipment itself have to be matched to the size of the plant, the product range and the market. In large-batch production, for example, a customized vehicle is required; in small-batch or unit production it is often necessary to manufacture a machine to specific customer requirements. Despite such great variations in the type of requirement, it is still possible to distinguish a number of common factors—one of them being the hierarchical structure of the automation landscape with objective and transparent distribution of information across all levels; from the control level for pre-production, assembly and transport up to the planning level for capacity planning and materials management.Hierarchical levels enable particular tasks to be assigned to specific automation equipment. Mainframes and minicomputers are used at the planning level. Dedicated systems such as numerical controls and programmable controllers are now used almost exclusively on the shopfloor control level.Local area networks connect the automation systems of different manufactures without the need for any adaptation. Protocols must be unified for this purpose. Since stable standards are not yet in existence, Siemens has decided to follow the strategy of standard harmonized development.Programmable controllers are part of all production, transport and storage systems. The main requirements are for control, operator communication, monitoring, counting and positioning. A comprehensive production family is a very important factor. Excellent hardware compatibility, easy interlinking and a uniform programming language are all characteristic of the family philosophy.Industrial robots are used mainly in the automobile industry. Largely thaks to them it is possible to produce economically and rationally any mix of model variants and to automate assembly. Programming facilities such as teach-in, on-line or off-line are therefore an important selection criterion for robot control.The majority of numerical controls in use today are used for controlling single machines in heavy-duty and special-purpose machinery manufacture. In networked applications, numerical controls form part of flexible manufacturing systems. In addition to machine control and management, the capacity for communication is an important criterion for selection in this case.In many controls for individual machines the priority is for quick and easy programming. “Shopfloor programming” has assumed considerable importance in such applications. Shopfloor programming requires controls with a sophisticated, user-friendly, graphics interface.Examples show how dedicated automation subsystems have been finding widespread application in the automation of manufacturing, transport and warehouse equipment. They are designed specially to perform certain tasks, both in programming and operation, in order to provide an economic solution to a problems in terms of matched performance and functionality.     

Minimizing the number of tardy jobs in the flowshop problem with operation and resource flexibility

In this paper, we propose a reformulation for the flowshop problem based on the concept of operation to workstation flexibility. While we assume a fixed sequence of operations in the reformulation, the “location” of each operation within the flow is not fixed. The proposed flowshop problem is important because the effective use of this flexibility can lead to significant changes in production performance. Solving the proposed problem involves two sub-problems: assignment of operations to workstations and sequencing of the jobs. We present a lower bound procedure and efficient solution approaches to solve each sub-problem. Furthermore, an improvement method based on neighborhood search and simulated annealing is implemented. A set of experiments is analyzed under different combinations of the proposed heuristics achieving high quality results. These experiments demonstrate that the heuristic factor is of significance for the problem.     

Production planning in semiconductor wafer fab considering variable cycle times

Recent research in the semiconductor manufacturing area has addressed some industrial engineering and operations research applications to solve the challenging production planning and scheduling problems. Relative to the other industries, the number of practical production management techniques and supporting software in the semiconductor industry is limited. The conventional models proposed use fixed or averaged cycle time and yield to get the results. However, in the actual wafer fabs, cycle time is spread widely and skewed due to the large variations in the operations. Therefore, the use of averaged cycle time and yield makes significant differences between the plan and the actual shop performance. Thus, we focus on the production planning problem in the wafer fabrication (“fab”), introducing a planning methodology that explicitly considers the variable cycle time and the shop status. We also evaluate some different types of input policies.     

Robust supply chain design under uncertain demand in agile manufacturing

This paper considers a supply chain design problem for a new market opportunity with uncertain demand in an agile manufacturing setting. We consider the integrated optimization of logistics and production costs associated with the supply chain members. These problems routinely occur in a wide variety of industries including semiconductor manufacturing, multi-tier automotive supply chains, and consumer appliances to name a few. There are two types of decision variables: binary variables for selection of companies to form the supply chain and continuous variables associated with production planning. A scenario approach is used to handle the uncertainty of demand. The formulation is a robust optimization model with three components in the objective function: expected total costs, cost variability due to demand uncertainty, and expected penalty for demand unmet at the end of the planning horizon. The increase of computational time with the numbers of echelons and members per echelon necessitates a heuristic. A heuristic based on a k-shortest path algorithm is developed by using a surrogate distance to denote the effectiveness of each member in the supply chain. The heuristic can find an optimal solution very quickly in some small- and medium-size cases. For large problems, a “good” solution with a small gap relative to our lower bound is obtained in a short computational time.     

Supply chain management with lean production and RFID application: A case study

This study applies lean production and radio frequency identification (RFID) technologies to improve the efficiency and effectiveness of supply chain management. In this study, a three-tier spare parts supply chain with inefficient transportation, storage and retrieval operations is investigated. Value Stream Mapping (VSM) is used to draw current state mapping and future state mapping (with lean production and RFID) with material, information, and time flows. Preliminary experiments showed that the total operation time can be saved by 81% from current stage to future stage with the integration of RFID and lean. Moreover, the saving in total operation time can be enhanced to 89% with cross docking. In addition, utilizing RFID technology, the cost of labors can be significantly reduced while maintaining current service capacity at the members in the studied supply chain. Return-on-investment (ROI) analysis shows that the proposed method is both effective and feasible.     

Developing a lean and agile work force

This article examines the contribution that human factors practitioners can make to improve work force capabilities in the lean and agile manufacturing environments. The article addresses the demands that lean and agile manufacturing initiatives will place on the current and emerging work force to achieve increasing levels of quality and flexibility with lower costs and shorter product life cycles. The issues of worker selection, continuous skill development, work place design, equipment maintenance, process improvement, mistake proofing, and process reconfiguration for new products are discussed from a human factors perspective. The article concludes that a new production system where human factors play a central role will be needed to help work force members achieve greater success in meeting these demands. © 1997 John Wiley & Sons, Inc.     

A heuristic approach for U-shaped assembly line balancing to improve labor productivity

The assembly line balancing problem is a non deterministic polynomial type planning problem for mass production. Layout design changes constitute a major decision that yields investment for assembly operations and numerous heuristics have been reported in the literature for solving the line balancing problems. U-shaped assembly layout offers several benefits over traditional straight-line layout in implementation of lean manufacturing and Just-In-Time technology. In the paper an attempt has been made to evaluate labor productivity in U-shaped line system and straight line system. A Critical Path Method (CPM) based approach for U-shaped assembly line has been applied for assigning the task to the work stations for assembly line layout. Results show that the CPM based U-shaped approach performs better and improve the labor productivity of assembly line layout.     

Non-hierarchical control of a flexible manufacturing cell

As hierarchically controlled computer-integrated manufacturing systems growthey tend to become complex and their designability, maintainability, expandability and fault tolerance deteriorate. As an alternative, herterarchical control architectures offer prospects of reduced compexity, reduced software development costs, high modularity, high flexibility, and improved fault tolerance. By locating decision making where information originates, global information is reduced to a minimum, scheduling becomes dynamic, machines and parts become “intelligent” entities that cooperatively interact, and the overall system is decomposed into functionally simplified, modular parts.Three flexible machining cell control systems have been constructed at the University of Wisconsin-Madison and are described in this paper: a centralized controller, a hierarchical controller with dynamic scheduling, and a fully distributed heterarchical controller with “intelligent parts”. Comparative results are reported showing that the heterarchical approach possesses a number of advantages including increased fault-tolerance, inherent adaptability and reconfigurability, decreased complexity, and reduced software development cost.     

ErgoVSM: A Tool for Integrating Value Stream Mapping and Ergonomics in Manufacturing

Value stream mapping (VSM) is a lean tool aiming at waste reduction. Previous research suggests that the use of VSM may result in work intensification and thus an increased risk for the workers of developing work‐related musculoskeletal disorders (MSD). In the current study, VSM was developed to also consider physical exposure in the analyzed production system (ErgoVSM). As the VSM, ErgoVSM is based on a participatory approach. ErgoVSM was tested in a Swedish manufacturing company. The results suggest that ErgoVSM catalyzes change processes to include intervention proposals emphasizing ergonomics in addition to waste reduction. Thus, ErgoVSM appeared useful for the investigated target group of production engineers and experienced operators. The performance improvements suggested when using the ordinary VSM seemed not to be hampered by adding the ergonomics complement. However, the use of ErgoVSM was somewhat more time consuming than the use of VSM. In conclusion, ErgoVSM is suggested as a feasible tool to be used by production engineers and experienced operators for including ergonomics considerations in the rationalization process.     

Hierarchical stochastic production planning for the highest business benefit

This paper addresses the hierarchical stochastic production planning (HSPP) problem of flexible automated workshops (FAWs), each with a number of flexible manufacturing systems (FMSs) the part-transfer between which is a delay of a time period. The problem not only includes uncertainties in the demand, capacities, material supply, processing times, necessity for rework, and scrap, but also considers multiple products and multiple time periods. The objective is to develop a production plan which tells each FMS how many parts to produce and when to produce them so as to obtain the highest business benefit. Herein, the HSPP problem is formulated by a stochastic nonlinear programming model whose constraints are linear but whose objective function is piecewise linear. For the convenience of solving the stochastic nonlinear programming model above, it is approximately transformed into a deterministic nonlinear programming model and further into a linear programming model. Because the scale of the model for a general workshop is too large to be solved by the simplex method on a personal computer within acceptable time, Karmarkar's algorithm and an interaction/prediction algorithm, respectively, are used to solve the model, the former for the medium or small scale problems and the latter for the large scale problems. By the implementation of the above-mentioned algorithms and through many HSPP examples, Karmarkar's algorithm, the interaction/prediction algorithm and the linear programming method in Matlab 5.0 are compared, the result of which shows that the proposed approaches are very effective and suitable for not only “push” production but also “pull” production.     

Robust manufacturing system design using multi objective genetic algorithms,Petri nets and Bayesian uncertainty representation

Decisions involving robust manufacturing system configuration design are often costly and involve long term allocation of resources. These decisions typically remain fixed for future planning horizons and failure to design a robust manufacturing system configuration can lead to high production and inventory costs, and lost sales costs. The designers need to find optimal design configurations by evaluating multiple decision variables (such as makespan and WIP) and considering different forms of manufacturing uncertainties (such as uncertainties in processing times and product demand). This paper presents a novel approach using multi objective genetic algorithms (GA), Petri nets and Bayesian model averaging (BMA) for robust design of manufacturing systems. The proposed approach is demonstrated on a manufacturing system configuration design problem to find optimal number of machines in different manufacturing cells for a manufacturing system producing multiple products. The objective function aims at minimizing makespan, mean WIP and number of machines, while considering uncertainties in processing times, equipment failure and repairs, and product demand. The integrated multi objective GA and Petri net based modeling framework coupled with Bayesian methods of uncertainty representation provides a single tool to design, analyze and simulate candidate models while considering distribution model and parameter uncertainties.     

Self‐managed work teams and manufacturing strategies: Cultural influences in the search for team effectiveness and competitive advantage

This article examines the relationship between manufacturing strategy and self‐managed work teams. The implementation of team working and lean production as a strategy designed to improve competitive advantage is juxtaposed with the cultural influences utilizing Hofstede's (1980) model of cultural dimensions. Case study material illustrates the contrasting positions posed by the different cultural and philosophical bases of lean production and self‐managed work teams. The resulting disequilibrium may explain why the implementation of teams in Western environments has proved less successful than anticipated in the manufacturing context. © 2001 John Wiley & Sons, Inc.     

Scheduling concurrent production over a finite planning horizon: polynomially solvable cases

The paper analyzes a manufacturing system made up of one workstation which is able to produce concurrently a number of product types with controllable production rates in response to time-dependent product demands. Given a finite planning horizon, the objective is to minimize production cost, which is incurred when the workstation is not idle and inventory and backlog costs, which are incurred when the meeting of demand results in inventory surpluses and shortages. With the aid of the maximum principle, optimal production regimes are derived and continuous-time scheduling is reduced to a combinatorial problem of sequencing and timing the regimes. The problem is proved to be polynomially solvable if demand does not exceed the capacity of the workstation or it is steadily pressing and the costs are “agreeable”.

Scope and purpose

Efficient utilization of modern flexible manufacturing systems is heavily dependent on proper scheduling of products throughout the available facilities. Scheduling of a workstation which produces concurrently a number of product types with controllable production rates in response to continuous, time-dependent demand is under consideration. Similar to the systems considered by many authors in recent years, a buffer with unlimited capacity is placed after the workstation for each product type. The objective is to minimize inventory storage, backlog and production costs over a finite planning horizon. Numerical approaches are commonly used to approximate the optimal solution for similar problems. The key contribution of this work is that the continuous-time scheduling problem is reduced to a combinatorial problem, exactly solvable in polynomial time if demand does not exceed the capacity of the workstation or the manufacturing system is organized such that the early production and storage of a product to reduce later backlogs are justified.     

Results of the Eureka FAMOS research programme: A European contribution to manufacturing technology

Market competition is leading to direct confrontation between products coming from the main manufacturing areas: Europe, the U.S.A. and Asia, where Japan is leading. For Europe to maintain and improve its role, it is important to develop “winning” products. This requires an advanced, technology based industry (secondary sector) and a highly effective research and innovation network (quaternarium), developing new design tools and new configurations for products and production systems. To foster and strengthen an advanced industry and a highly effective quaternarium, Europe has launched various initiatives, from EEC Programmes to the Eureka initiative.In this paper the contribution of the Eureka FAMOS projects is assessed by using a model linking the research innovation cycle, “actors” (companies and research institutions) and activation mechanisms (programmes and initiatives). With the Eureka FAMOS Umbrella Project acting as an activation mechanism, the analysis of the specific FAMOS projects carried out through MONITECH—an assessment activity set up by IMU-CNR—shows how the “actors” (companies and research institutions) have reacted and launched specific projects (36 at an estimated cost of 600 MECU), in 17 industrial sectors, leading to new production paradigms (production systems and related technologies). Considering the results already achieved (pilot production systems and technologies) the Eureka FAMOS Research Programme may be seen as a relevant European initiative in manufacturing technology.The synergy which the Eureka FAMOS Programme is starting to provide with EEC Programmes will give the European research network and industry further benefits.     

Structurally noise resistant classifier for multi-modal person verification

In this letter we propose a piece-wise linear (PL) classifier for use as the decision stage in a two-modal verification system, comprised of a face and a speech expert. The classifier utilizes a fixed decision boundary that has been specifically designed to account for the effects of noisy audio conditions. Experimental results on the VidTIMIT database show that in clean conditions, the proposed classifier is outperformed by a traditional weighted summation decision stage (using both fixed and adaptive weights). Using white Gaussian noise to corrupt the audio data resulted in the PL classifier obtaining better performance than the fixed approach and similar performance to the adaptive approach. Using a more realistic noise type, namely “operations room” noise from the NOISEX-92 corpus, resulted in the PL classifier obtaining better performance than both the fixed and adaptive approaches. The better results in this case stem from the PL classifier not making a direct assumption about the type of noise that causes the mismatch between training and testing conditions (unlike the adaptive approach). Moreover, the PL classifier has the advantage of having a fixed (non-adaptive, thus simpler) structure.