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.     

Robust design of flexible manufacturing systems using, colored Petri net and genetic algorithm

A method is presented for the robust design of flexible manufacturing systems (FMS) that undergo the forecasted product plan variations. The resource allocation and the operation schedule of a FMS are modeled as a colored Petri net and an associated transition firing sequence. The robust design of the colored Petri net model is formulated as a multi-objective optimization problem that simultaneously minimizes the production costs under multiple production plans (batch sizes for all jobs), and the reconfiguration cost due to production plan changes. A genetic algorithm, coupled with the shortest imminent operation time (SIO) dispatching rule, is used to simultaneously find the near-optimal resource allocation and the event-driven schedule of a colored Petri net. The resulting Petri net is then compared with the Petri nets optimized for a particular production plan in order to address the effectiveness of the robustness optimization. The simulation results suggest that the proposed robustness optimization scheme should be considered when the products are moderately different in their job specifications so that optimizing for a particular production plan creates inevitably bottlenecks in product flow and/or deadlock under other production plans.     

Prevalence and associated risk factors of low‐back pain in textile fishing net manufacturing

This study examined the 7‐day prevalence of low‐back pain (LBP; i.e., pain within the preceding week of the survey) and identified associated factors, including working posture, for a population of fishing net assembly workers. LBP is a serious problem in manual work with high prevalence and affects worker absenteeism. A cross‐sectional survey study was conducted among textile fish net industrial workers using a structured questionnaire (hand delivered by researchers and independently completed by workers). The 7‐day prevalence of LBP in this study was 68.6% (95% confidence interval [CI]: 65 to 72%). Work factors significantly related to LBP included prolonged standing and walking. Workers 35 years old or greater were significantly more likely to experience LBP within the past 7 days preceding the survey than were those 34 years old or less (adjusted odds ratio [ORadj] = 4.9; 95% CI: 2.4 to 10.3; p = .0001). Other significant factors associated with LBP included posture position, specifically stooping (ORadj = 1.6; 95% CI: 1.0 to 2.3; p = .033), lifting (ORadj = 1.6; 95% CI: 1.1 to 2.4; p = .025), and high concentration jobs (ORadj = 1.9; 95% CI: 1.3 to 2.7; p = .001), respectively. LBP among textile fish net workers is a serious problem meriting ergonomic evaluation and design of control measures for reducing worker exposure to risk factors. Work characteristics were more significantly associated with LBP than were individual characteristics. Factories need to consider adjusting work conditions to prevent worker low‐back injuries. © 2012 Wiley Periodicals, Inc.     

Holarchy formation and optimization in holonic manufacturing systems with contract net

Holonic manufacturing systems (HMS) is based on the notion of holon, an autonomous, cooperative and intelligent entity to provide a econfigurable, flexible and decentralized manufacturing environment to respond to changing needs and opportunities. A set of holons that cooperate to achieve a goal forms a holarchy. How to design a mechanism to form a holarchy to achieve a goal while minimizing the overall cost is a challenge. The objectives of this paper are to propose models and develop collaborative algorithms to guide the holons to form a holarchy to coherently move toward the desired goal state ultimately. We adopt contract net protocol (CNP) to model mutual selection of holons in forming a holarchy. We formulate a holarchy optimization problem to minimize the cost subject to the feasibility constraints. To analyze the feasibility of a holarchy, a Petri net (PN) model is proposed. As classical PN models do not take into account the cost involved in firing transitions, we augment the PN model with cost functions in the problem formulation. Due to the distributed architecture of HMS, the internal structure of each potential holarchy that acts as bidder in CNP is not available to the manager. A key issue is to determine the feasibility of a holarchy without constructing the whole PN model of the given hierarchy. We study the feasible conditions for a holarchy and propose a collaborative algorithm to analyze the feasibility and award contracts to holons without constructing the whole model of a holarchy.     

An extended model of design process of lean production systems by means of process variables

In this paper, we present an axiomatic modeling of lean production system design, using process variables (PVs). So far, we had developed a model for conceptual design of lean production systems by means of FR–DP relationships, the key characteristics of axiomatic design (AD) methodology, appeared in the proceedings of Second International Conference of Axiomatic Design. Albeit the model in question was thorough enough to be applied in various cases, its embedded abstract principles hamper straightforward applications and the required resources, tools, and techniques are not clarified. In AD terms, it lacks PVs created by mapping the design parameters (DPs) to the process domain to clarify the means that produce the specified DPs. Owing to the difficulties involved in the definition of PVs for manufacturing systems, there is few works in this area. This paper is an attempt to introduce PVs in production system design. When we are developing a product (i.e. a part), we can simply interpret the set of PVs as the process design. In the case of a production system we interpret PVs as the tools, methods, and resources, required for implementing a lean production system. In this paper, according to AD methodology, we have developed a hierarchical structure to model the design process of a lean production system, composed of FRs, DPs, and PVs. Serving as an efficient guideline for the design process and clarifying the required tools, methods, and resources, this structure is general enough to be applied for different cases.     

Multiple-objective scheduling and real-time dispatching for the semiconductor manufacturing system

Implementing efficient scheduling and dispatching policies is a critical means to gain competitiveness for modern semiconductor manufacturing systems. In contemporary global market, a successful semiconductor manufacturer has to excel in multiple performance indices, consequently qualified scheduling approaches should provide efficient and holistic management of wafer products, information and manufacturing resources and make adaptive decisions based on real-time processing status to reach an overall optimized system performance. To cope with this challenge, a timed extended object-oriented Petri nets (EOPNs) based multiple-objective scheduling and real-time dispatching approach is proposed in this paper. Four performance objectives pursued by semiconductor manufacturers are integrated into a priority-ranking algorithm that serves as the initial scheduling guidance, and then all wafer lots will be dynamically dispatched by the hybrid real-time dispatching control system. A set of simulation experiments validate the proposed multiple-objective scheduling and real-time dispatching algorithm may achieve satisfactory performances.     

Autonomy-subnet based structural synthesis and liveness guarantying policy of Petri net model of flexible manufacturing system

In this paper, an autonomous subnet based structural methodology forbottom-up synthesis of Petri Nets for Flexible Manufacturing Systems is proposed.Furthermore, the theoretical analysis of the model constructed by the method is carried byintensively using model's structural information, such as invariants, siphons, etc.. As aresult, the analysis leads us to draw the general conclusion that the model obtained isconservativeness and thus bound, and characterize its liveness in terms of zero-markingminimal siphons. It is based on model's structural information that distinguishes ourmethod from others. in line of this thought, a liveness guarantying policy for the obtainedmodel is proposed. Some control subnets are merged into the original model according tothe proposed synthesis rules in this paper to ensure that no minimal siphons are emptiedin any state, therefore the liveness is guaranteed. As a result, a live, conservative andrevertible Petri Nets is obtained. A practical example is also presented to     

Evaluation of the role of waste in a truck manufacturing line using simulation

In their never-ending search to improve manufacturing performance, companies try to eliminate all sources of waste. In this paper, we describe how the effects of the elimination of waste on performance measures such as lead time and overtime costs can be estimated using logistical simulation. This is illustrated using a real-life case study that was conducted in the repair department of a truck cabin factory. In this department, cabs are controlled and if necessary repaired. The first part of the paper describes how bottlenecks were determined for both the present layout and for a proposed layout change. This turned out to be difficult, as several product flows intertwine. Modelling was made complex by these interactions, as they caused deadlock phenomena. The second part of the paper represents a sensitivity analysis, which evaluates the effects of different types of waste, such as machine breakdowns, inadequate buffer size and production time variance.     

Petri net based process scheduling: A model of the control system of flexible manufacturing systems

In this paper, we propose a class of algorithms for the sub-optimal solution of a particular class of problems of process scheduling, particularly focusing on a case study in the area of flexible manufacturing systems (FMSs). The general class of problems we face in our approach is characterized as follows: there is a set of concurrent processes, each formed by a number of temporally related tasks (segments). Tasks are executable by alternate resource sets, different both in performance and costs. Processes and tasks are characterized by release times, due dates, and deadlines. Time constraints are also present in the availability of each resource in resource sets. It has been proven that such a problem does not admit an algorithm for an optimal solution in polynomial time. Our proposed algorithm finds a sub-optimal schedule according to a set of optimization criteria, based on task and process times (earliness, tardiness), and/or time independent costs of resources. Our approach to process scheduling is based on Timed Coloured Petri Nets. We describe the structure of the coordination and scheduling algorithms, concentrating on (i) the general-purpose component, and (ii) the application-dependent component. In particular, the paper focuses on the following issues: (i) theautomatic synthesis of Petri net models of the coordination subsystem, starting from the problem knowledge base; (ii) the dynamic behavior of the coordination subsystem, whose kernel is a High Level Petri net executor, a coordination process based on an original, general purpose algorithm; (iii) the structure of the real-time scheduling subsystem, based on particular heuristic sub-optimal multi-criteria algorithms. Furthermore, the paper defines the interaction mechanisms between the coordination and scheduling subsystems. Our approach clearly distinguishes the mechanism of the net execution from the decision support system. Two conceptually distinct levels, which correspond to two different, interacting implementation modules in the prototype CASE tool, have been defined: theexecutor and thescheduler levels. One of the outstanding differences between these levels is that the executor is conceived as a fast, efficient coordination process, without special-purpose problem-solving capabilities in case of conflicts. The scheduler, on the other hand, is the adaptive, distributed component, whose behavior may heavily depend on the problem class. If the scheduler fails, the executor is, in any case, able to proceed with a general-purpose conflict resolution strategy. Experimental results on the real-time performance of the kernel of the implemented system are finally shown in the paper. The approach described in this paper is at the basis of a joint project with industrial partners for the development of a CASE tool for the simulation of blast furnaces.     

A complete cellular manufacturing system design methodology based on axiomatic design principles

This paper provides a framework and a road map for people who are ready to transform their traditional production system from process orientation to cellular orientation, based on Axiomatic Design (AD) principles. A feedback mechanism for continuous improvement is also suggested for evaluating and improving the cellular design against pre-selected performance criteria. A complete implementation of the proposed methodology at a manufacturing company and resulting performance improvements are also provided.     

The Operations-Time Chart: A graphical tool to evaluate the performance of production systems – From batch-and-queue to lean manufacturing

In this paper, we describe the spreadsheet modeling of manufacturing systems by means of the Operations-Time Chart (hereafter, OT-Chart), a graphical tool for an automatic time-phased representation and measurement of the operation of production systems, developed by the authors. In order to improve the design of a production system, it is necessary to know the key performance metrics of the system (productivity, lead-time, inventories, downtimes and wait times) and identify the effects of design parameters on system performance. Calculating some of these magnitudes can be very complicated, especially for production systems involving multiple and confluent processes, with different cycle times and lot sizes. The OT-Chart permits a visual tracking of the aforementioned parameters throughout each process, and like a simulation tool, the program calculates and displays the effects of changing input parameters. A special version of the Chart has been designed for lean manufacturing environments, where visual tools are much appreciated. The OT-Chart provides tracking of different types of waste and supports inventory supermarkets and pull scheduling. The paper includes a case study: a plant is redesigned from a conventional batch-and-queue production system into a lean manufacturing system with the help of the OT-Chart (it is used to test the performance of each layout) allowing managers to evaluate and refine their designs.     

Lean rules extraction methodology for lean PSS design via key performance indicators monitoring

Lean PSS (Product-Service System) design comprises a promising strategy for delivering sustainable PSS offerings, considering several well-established lean practices. However, automated ways to apply lean practices and more specifically lean rules in industry are limited. This work proposes a methodology for improving the leanness of PSS design, by combining real-time KPI monitoring with lean principles and practices. Through a correlation of typical wastes with the metrics used in the calculation of KPIs, the Total Leanness Index (TLI) of the procedures is defined. Based on automatically identified trade-off values for TLI, lean rules are extracted to improve the performance of PSS lifecycle phases. The proposed lean rules extraction methodology (LeanREM) is validated through a case study of power waste reduction and the concurrently maintenance time decrease in a mould-making company.     

A two phase optimization method for Petri net models of manufacturing systems

Optimization is a key issue in the design of large manufacturing systems. An adequate modeling formalism to express the intricate interleaving of competition and cooperation relationships is needed first. Moreover, robust and efficient optimization techniques are necessary. This paper presents an integrated tool for the automated optimization of DEDS, with application to manufacturing systems. After a very quick overview of optimization problems in manufacturing systems, it presents the integration of two existing tools for the modeling and evaluation with Petri nets and a general-purpose optimization package based on simulated annealing. The consideration of a cache and a two phase technique for optimization allows to speed-up the optimization by a factor of about 35. During the first preoptimization phase, a rough approximation of the optimal parameter set is computed based on performance bounds. Two application examples show the benefits of the proposed technique.     

Comparison of layered cellular manufacturing system design approaches

In this study, a mathematical programming approach is proposed to design a layered cellular manufacturing system in highly fluctuated demand environment. A mathematical model is developed to create dedicated, shared and remainder cells with the objective of minimizing the number of cells. In contrast with classical cellular manufacturing systems, in layered cellular systems, some cells can serve to multiple part families. A five-step hierarchical methodology is employed: (1) formation of part families, (2) calculation of expected cell utilizations and demand coverage probabilities, (3) specification cell types as dedicated, shared, and remainder cells, (4) simulation of proposed layered systems to evaluate their performance with respect to average flowtime and work-in-process inventory, and (5) statistical analysis to find the best layered cellular design among alternatives. It is found that designs with higher number of part families tend to have less number of machines. Similar results are also observed with respect to average flowtime and work-in-process inventory measures. The results are also compared with a heuristic approach from the literature. None of the approaches is dominant with respect to all of the performance measures. Mathematical modeling approach performs better in terms of number of machines for most of the alternative designs. However, heuristic approach yields better average flowtime and work-in-process inventory for most of the designs.     

An intelligent simulation environment for manufacturing systems

The manufacturing field is an area where the application of simulation is an essential tool for validating methods and architectures before applying them on the factory floor. Despite the fact that there are a great number of simulation tools, most of them do not take into account the specific requirements of the “new manufacturing era” such as distributed organization, interoperability, cooperation, scalability, fault tolerance and agility. On the other hand, Multiagent System technology has demonstrated its utility in manufacturing system modeling and implementation. Agenthood features such as proactivity, reactivity, and sociability may also be useful for associating them with the specific simulation needs of the new changing requirements for manufacturing systems. In this paper, an Agent-supported Simulation Environment for intelligent manufacturing systems is presented. The different roles that are played by the agents of the simulation environment are defined taking into account the specific dynamic features in manufacturing simulation and the requirements of the new manufacturing era. Moreover, the interaction and cooperation scenarios among these agents are specified to facilitate manufacturing simulation in an appropriate and flexible way. A detailed evaluation study, with regards to the new manufacturing era requirements, demonstrates the advantages of the proposed approach over current state-of-the-art proposals.     

Expert systems for manufacturing cell simulation and design

Computer Integrated Manufacturing (CIM) is approached by means of the application of Computer Aided Design (CAD), Computer Aided Manufacturing (CAM) and other CA techniques, methods and programs/program systems. These programs are often implemented as knowledge-based, or expert systems and in this way they became typical examples of engineering application of artificial intelligence. The production task of CIM systems is solved by using flexible manufacturing systems (FMSs). FMSs built up from smaller, complex units, i.e. from flexible manufacturing cells (FMCs) have several advantages. The design and the operation of manufacturing systems need new, sophisticated methods to utilize all the embedded benefits of the sophisticated and expensive elements installed for production purposes. New methods like knowledge processing technology, cooperative problem-solving techniques, etc., offer wide possibilities to design more reasonable systems. This paper describes prototype expert systems that make use of different knowledge-based tools and techniques to design (configure, reconfigure) and simulate manufacturing cells, taking into consideration technological plans and other relevant information.     

A lab-scale manufacturing system environment to investigate data-driven production control approaches

Controlling production and release of material into a manufacturing system effectively can lower work-in-progress inventory and cycle time while ensuring the desired throughput. With the extensive data collected from manufacturing systems, developing an effective real-time control policy helps achieving this goal. Validating new control methods using the real manufacturing systems may not be possible before implementation. Similarly, using simulation models can result in overlooking critical aspects of the performance of a new control method. In order to overcome these shortcomings, using a lab-scale physical model of a given manufacturing system can be beneficial. We discuss the construction and the usage of a lab-scale physical model to investigate the implementation of a data-driven production control policy in a production/inventory system. As a data-driven production control policy, the marking-dependent threshold policy is used. This policy leverages the partial information gathered from the demand and production processes by using joint simulation and optimization to determine the optimal thresholds. We illustrate the construction of the lab-scale model by using LEGO Technic parts and controlling the model with the marking-dependent policy with the data collected from the system. By collecting data directly from the lab-scale production/inventory system, we show how and why the analytical modeling of the system can be erroneous in predicting the dynamics of the system and how it can be improved. These errors affect optimization of the system using these models adversely. In comparison, the data-driven method presented in this study is considerably less prone to be affected by the differences between the physical system and its analytical representation. These experiments show that using a lab-scale manufacturing system environment is very useful to investigate different data-driven control policies before their implementation and the marking-dependent threshold policy is an effective data-driven policy to optimize material flow in manufacturing systems.     

Coordinated scheduling of production and logistics for large-scale closed-loop manufacturing using Benders decomposition optimization

This paper studies coordinated scheduling of production and logistics for a large-scale closed-loop manufacturing system by integrating its manufacturing and recycling process. In addition to the forward manufacturing process, different recycling units in reverse recycling process are also studied. A decentralized network is designed to formulate the coordinated scheduling problem as a mixed integer programming model with both binary and integer variables. As the problem for closed-loop manufacturing is large-scale and computational-consuming in nature, the model is divided into integer variable sub-models and complex binary variable sub-models for preprocessing and reprocessing respectively. An iterative solution approach by Benders decomposition is developed to accelerate the solving efficiency in large-scale case by updating custom constraints. A case study is conducted to investigate the managerial implications of the decentralized network for the closed-loop manufacturing system. Computational experiments demonstrate the validity and efficiency of the proposed iterative solution approach for the large-scale scenarios.     

Hierarchical control system design using approximate simulation

In this paper, we present a new approach for hierarchical control based on the recent notions of approximate simulation and simulation functions, a quantitative version of the simulation relations. Given a complex system that needs to be controlled and a simpler abstraction, we show how the knowledge of a simulation function allows us to synthesize hierarchical control laws by first controlling the abstraction and then lifting the abstract control law to the complex system using an interface. For the class of linear control systems, we give an effective characterization of the simulation functions and of the associated interfaces. This characterization allows us to use algorithmic procedures for their computation. We show how to choose an abstraction for a linear control system such that our hierarchical control approach can be used. Finally, we show the effectiveness of our approach on an example.     

A hierarchic approach to production planning and scheduling of a flexible manufacturing system

The paper deals with the problem of improving the machine utilization of a flexible manufacturing cell. Limited tool magazine space of the machines turns out to be a relevant bottleneck. A hierarchic approach for this problem is proposed. At the upper level, sets of parts that can be concurrently processed (batches) are determined. At the lower levels, batches are sequenced, linked, and scheduled. Methods taken from the literature are used for the solution of the latter subproblems, and an original mixed integer programming model is formulated to determine batches. The proposed methods are discussed on the basis of computational experience carried out on real instances.