The tooling system configuration in a new manufacturing system architecture

A new manufacturing system architecture, called Mod Flex Prod (MFP), has been recently proposed to match the balance between productivity and flexibility required by suppliers of components for the automotive industry. Among the relevant issues that cause the new architecture to be more profitable than transfer lines and flexible manufacturing systems, tooling has been shown to have an important role. Starting from this result, this paper deepens the advantages in tooling attainable with the new architecture. In particular, it presents a new approach for configuring the tooling system (i.e. selecting the number of tool copies for each tool type) which takes into account that tool copies can be required by the machines to perform operations, by the tool carrier to transport tools within the system and by the tool room when inserts have to be reconditioned. With reference to a real case study, the new approach allows one to assess that tooling investment can be reduced by about 20% if the new architecture replaces traditional flexible manufacturing systems.     

A bottleneck-based beam search for job scheduling in a flexible manufacturing system

In this paper, we study job-scheduling methods for flexible manufacturing systems (FMSs). Routeing flexibility is a feature that distinguishes FMS scheduling from a classic general jobshop problem. We formalize the problem as a flexible jobshop problem and introduce a flexibility index to measure the extent of routeing flexibility. Based on a procedure to identify a potential bottleneck machine, we develop a beam search method for approximately solving the problem. The proposed method yields a significantly shorter makespan than that of the commonly used shortest processing-time dispatching rule, and it properly exploits the added flexibility in routeing. The computational effort required also is small enough to enable practical implementation.     

A real-time scheduling mechanism for a flexible manufacturing system: Using simulation and dispatching rules

This paper presents a real-time scheduling methodology which uses simulation and dispatching rules for flexible manufacturing systems. We develop a scheduling mechanism in which job dispatching rules vary dynamically based on information from discrete event simulation that is used for evaluating candidate dispatching rules. In this paper, we improve and extend a previous research on simulation-based real-time scheduling by suggesting a more systematic framework for the scheduling mechanism through refinement of functions of modules in the mechanism, and by presenting and analysing various scheduling strategies used to operate the mechanism. The strategies are formed by combining two factors that might influence the performance of the mechanism: type of simulation model which is used in the mechanism and points of time when new dispatching rules are selected. In order to compare performance of the scheduling strategies, computational experiments are performed and results are reported.     

Mixed-Integer Linear Programming approaches to shelf-life-integrated planning and scheduling in yoghurt production

In the production of perishable products such as dairy, meat or bakery goods, the consideration of shelf life in production planning is of particular importance. Retail customers with relatively low inventory turns can benefit significantly from longer product shelf life as wastage and out-of-stock rates decrease. However, in today's production planning and control systems, shelf-life issues with regard to specific products or customers are only seldom accounted for. Therefore, the objective of this paper is to develop Mixed-Integer Linear Programming (MILP) models that integrate shelf-life issues into production planning and scheduling. The research is based on an industrial case study of yoghurt production. Relying on the principle of block planning, three different MILP models for weekly production planning are presented that apply a combination of a discrete and continuous representation of time. Overnight production and, hence, the necessity for identifying two different shelf-life values for the same production lot is included in the model formulation. Numerical experiments show that near-optimal solutions can be obtained within reasonable computational time.     

Structured adaptive supervisory control model and software development for a flexible manufacturing system

A three-step approach is proposed to substantially reduce the high cost of development of control software for an FMS on the shop floor. First, by introducing the concept of multiple computing processes into Automata Theory, a finite capacity machine (FCM) is presented as an extended finite machine. An FCM is used to model the control of a flexible manufacturing system, which avoids the state explosion problem. Secondly, a structured adaptive supervisory control (SASC) model meeting the desired control objectives for an FMS is derived from a composed FCM. The SASC model can be constructed systematically. Finally, generic software components for an SASC model are described, which allow the SASC model to be cost-effectively transferred into shop-floor applicable control software.     

Real-time scheduling in manufacturing system with machining and assembly operations: a state of art

Manufacturing systems producing multiple products are common in many industries, where products are made from several parts and/or sub-assemblies that require machining operations in first stage and assembly operations at later stage. Several scheduling techniques are proposed in the literature for such manufacturing system to develop near optimal schedule. A disruption in the manufacturing necessitates adjusting previously planned schedule which is known as real-time scheduling. This paper presents a comparative evaluation of different scheduling methods proposed by different investigators for dealing such situations. The literature indicates that real-time scheduling of manufacturing system with machining and assembly operations is hardly attempted. The paper offers a framework for developing rescheduling methodologies for such manufacturing situations.     

Tool requirements planning in a flexible manufacturing system: Minimizing tool costs subject to a makespan constraint

We consider a tool requirements planning problem (TRPP) of determining the number of tool copies for each tool type in a flexible manufacturing system with an automatic tool transporter. In this paper, four heuristic algorithms are developed for the TRPP with the objective of minimizing the total tool purchase cost subject to a makespan constraint. In the algorithms, starting from an initial (infeasible) solution, the numbers of tool copies for certain tool types are increased at each iteration until the makespan constraint becomes satisfied. In these algorithms, information obtained from discrete event simulation is used to select tool types of which the numbers of copies are to be increased. Computational experiments are performed on randomly generated test problems and results show that good tool requirements plans can be obtained with the heuristic algorithms in a reasonable amount of computation time.     

A new heuristic algorithm for capacity planning in a manufacturing facility under learning

In this paper, a new and efficient heuristic algorithm is presented to determine the production capacity in a new facility under the effect of learning. Different demand patterns are studied while deciding the capacity requirements. Further, the learning effects due to human-machine interaction often found in a manufacturing system are considered during the development of the model. A computer program is developed and interfaced with XMP software on a Sun 3/60 workstation. Several numerical examples are presented to illustrate the heuristic algorithm.     

A prototype safety system for new on-the-job training (OJT) in an anthropocentric cell manufacturing system

The anthropocentric cell manufacturing system (ACMS) discussed consists of a skill-based manufacturing scheduling system, a new on-the-job training (New OJT) system and a safety system. The New OJT was developed using e-learning and automated guided vehicle (AGV)-arm robot as a teacher for CNC machine training. Since the machines and the AGV-arm robot are automatic devices, controlled by computer programs, the dangers might arise during training. Therefore, the safety system is required to ensure that a learner will be safe. We propose a prototype of safety system with designed machine-protection in order to protect the learner from dangerous behaviours during a level 1 training of a New OJT in ACMS. The machine-protection focused on protection from danger using image processing with a background subtraction technique and comparison of objects' position. We also evaluated safety assessments of the learners, consisting of human error probabilities (HEP) and a human error rate (HER). The prototype of this developed safety system showed that the machine-protection certainly raises a warning alarm when the learner rises into dangerous zones during the training. The evaluated safety assessments showed that our designed New OJT training level 1 course performed more efficient safety performance for self-training of the learner.     

A prototype safety system for new on-the-job training (OJT) in an anthropocentric cell manufacturing system

The anthropocentric cell manufacturing system (ACMS) discussed consists of a skill-based manufacturing scheduling system, a new on-the-job training (New OJT) system and a safety system. The New OJT was developed using e-learning and automated guided vehicle (AGV)-arm robot as a teacher for CNC machine training. Since the machines and the AGV-arm robot are automatic devices, controlled by computer programs, the dangers might arise during training. Therefore, the safety system is required to ensure that a learner will be safe. We propose a prototype of safety system with designed machine-protection in order to protect the learner from dangerous behaviours during a level 1 training of a New OJT in ACMS. The machine-protection focused on protection from danger using image processing with a background subtraction technique and comparison of objects’ position. We also evaluated safety assessments of the learners, consisting of human error probabilities (HEP) and a human error rate (HER). The prototype of this developed safety system showed that the machine-protection certainly raises a warning alarm when the learner rises into dangerous zones during the training. The evaluated safety assessments showed that our designed New OJT training level 1 course performed more efficient safety performance for self-training of the learner.     

An integrated model for inventory and production planning in a two-stage hybrid production system

A two-stage hybrid flow-shop production system is considered. The first stage is a process production system and the second stage is a job-shop production system. The two stages are separated by an intermediate warehouse to introduce flexibility (some independence) in the planning of production at both stages. The inventory level at the warehouse should be optimized to provide a trade-off between the cost of carrying the inventory of the semi-finished products, the minimum batch size requirement in the first stage, and the required service level at the second stage. An integrated model for planning the production in these hybrid flow-shop production systems types is developed. The objectives of optimizing the production and inventory costs at the two stages of the system, including the warehouse, while satisfying customer demands, are considered. An algorithm to solve the suggested model is described in detail, and a solution is provided for a real world case, which has inspired the study. A computational study to measure the performance of the approach was also carried out and the results are reported.     

Lagrangean relaxation approach to joint optimization for production planning and scheduling of synchronous assembly lines

This paper focuses on simultaneous optimisation of production planning and scheduling problem over a time period for synchronous assembly lines. Differing from traditional top-down approaches, a mixed integer programming model which jointly considers production planning and detailed scheduling constraints is formulated, and a Lagrangian relaxation method is developed for the proposed model, whereby the integrated problem is decomposed into planning, batch sequencing, tardiness and earliness sub-problems. The scheduling sub-problem is modelled as a time-dependent travelling salesman problem, which is solved using a dynasearch algorithm. A proposition of Lagrangian multipliers is established to accelerate the convergence speed of the proposed algorithm. The average direction strategy is employed to solve the Lagrangian dual problem. Test results demonstrate that the proposed model and algorithm are effective and efficient.     

Development of a new production management system for the co-elevation of humanity and productivity

This paper reports development activities for a new production management system aiming to obtain excellent product quality and high productivity by heightening the morale of the workers and by harmonizing the workers' human needs with the company's organizational needs

In the course of proceeding with the development of the new production management system, first, the needs of workers as a whole and as individuals were analysed by the multivariate analysis method, so as to clarify the differences in their motivations in regards of the workers' attributes, working environments and the management systems

Secondly, several proposals for improvement were presented to workers as a whole and as individuals and such proposed improvements were experimentally implemented one after another in order to harmonize the human needs with the organizational needs.     

Decomposition in automatic generation of Petri nets for manufacturing system control and scheduling

Despite the efforts in developing Petri net models for manufacturing control and scheduling, the generation of Petri net models cannot be automated for agile manufacturing control and scheduling without difficulties. The problems lie in the complexity of Petri net models. First of all, it is difficult to visualize the basic manufacturing process flow in a complex Petri net model even for a Petri net modelling expert. The second problem is related to the complexity of using Petri net models for manufacturing system scheduling. In this paper, a decomposition methodology in automatic generation of Petri nets for manufacturing system control and scheduling is developed. The decomposition methodology includes representing a manufacturing process with the Integrated Definition 3 (IDEF3) methodology, decomposing the manufacturing process based on the similarity of resources, transforming the IDEF3 model into a Petri net control model, and aggregating sub Petri net models. Specifically, a sequential cluster identification algorithm is developed to decompose a manufacturing system represented as an IDEF3 model. The methodology is illustrated with a flexible disassembly cell example. The computational experience shows that the methodology developed in this paper reduces the computational time complexity of the scheduling problem without significantly affecting the solution quality obtained by a simulated annealing scheduling algorithm. The advantages of the methodology developed in this paper include the combined benefits of simplicity of the IDEF3 representation of manufacturing processes and analytical and control properties of Petri net models. The IDEF3 representation of a manufacturing process enhances the manmachine interface.     

Congruence of manufacturing decision areas in a production system: a research framework

A well designed production system secures environmental and internal fit. Environmental fit in a production system refers to alignment of manufacturing decisions to the external settings such as product and market. Internal fit implies that manufacturing decisions are mutually supportive. This paper develops a framework to analyse congruence of manufacturing decision areas in a production system. The framework considers six broad manufacturing decision areas. Based on the literature review, 54 decision types and alternative decision choices for each decision type are identified. The subjective and/or objective constructs to measure decision type are presented which should be useful in designing construct and in data gathering to conduct empirical research. Using the proposed framework, many research questions concerning the settings of several decision types for a specific type of production system can be generated and empirically tested.     

Development of an automated process planning and production activity control system for the manufacturing of engineered work surfaces

This paper describes the design and implementation of an Automated Process Planning and Production Activity Control system for a make-to-order business and presents a formal methodology for the development of integrated manufacturing systems. The research is based on concepts developed in a project undertaken in a job shop Case Study facility, producing precision-engineered work surfaces. Industry today is facing numerous challenges on many fronts demanding improved availability and dissemination of processing information. On the demand side there is increased pressure on the manufacturer to meet deadlines and provide the customer with a prompt, efficient service, with accurate lead-time information, and a product of the utmost quality, on time. On the supply side there is increasing competition, variety in the market, a diverse product range, varying processing times and extremely short lead times. The nature of today's business world means that real-time information is a requirement and not an extra. This paper documents the design, structure and implementation of an Automated Process Planning system, which completely automates and integrates Order Entry stages from order receipt to order release. The developed system, namely the Manufacturing Optimization Information System, or MOIS, relays information to and from shop floor operators via a Production Activity Control system at each of the manufacturing stations. The MOIS is part of ongoing research endeavouring to integrate order processing, Process Planning and production control activities with a combined dynamic scheduling and material optimization module in a holistic manufacturing optimization system. The two specific aims of this paper are very clear; first, to bridge the theory-practice gap between theoretical concepts and real industrial issues surrounding Process Planning and Production Control. Secondly, to outline the design, structure and evolution of an integrated Automatic Process Planning and Production Activity Control system, installed in a make-to-order enterprise.     

An integrated approach for production and distribution planning in supply chain management

Many firms have been trying to optimize their production and distribution systems separately, but using this approach limits any possible increase in profit. Thus, it is becoming more important to analyse these two systems simultaneously. This paper presents the solutions for integrated production and distribution planning and investigates the effectiveness of their integration through a computational study, in a multi-plant, multi-retailer, multi-item, and multi-period logistic environment where the objective is to maximize the total net profit. Computational results on test problems using the proposed heuristic confirm the substantial advantage of the integrated planning approach over the decoupled one. Sensitivity analysis on the input parameters indicates that, under the right conditions, the effectiveness of integrating production and distribution functions can be extremely high.     

Real-time disruption management in a two-stage production and inventory system

This paper presents a general disruption management approach for a two-stage production and inventory control system. A penalty cost for deviations of the new plan from the original plan is incorporated and the concept of a disruption recovery time window is introduced. We define two classes of problems: one with fixed setup epochs and another with flexible setup epochs. With linear or quadratic penalty functions for production/ordering quantity change and fixed setup epochs, the best recovery plan is obtained by solving a quadratic mathematical programming problem. With convex penalty functions for quantity changes and flexible setup epochs, it is shown that the second stage orders have identical order quantities within each production cycle. Therefore, in a lot-for-lot system, the ordering and production quantities for both stages are the same. As a special case, we consider disruption recovery problems with short time windows spanning one or two production cycles. We also discuss solution procedures for both major and minor disruption problems and give an extension for the case of multiple retailers. Throughout the paper managerial insights are presented that indicate how a company should respond to various types of disruptions during its operations.     

Machine learning based adaptive production control for a multi-cell flexible manufacturing system operating in a random environment

An adaptive production control approach is used for controlling a multi-cell FMS with machines subject to failures, operating in a highly changing produce-toorder environment. A probabilistic machine learning procedure is integrated within a two-level Distribution Production Control System (DPCS). This enables the DPCS to adapt itself to large fluctuations in demand as well as to other stochastic factors. An extensive simulation study shows that the proposed adaptive control approach significantly improves the production system performance in terms of a combined measure of throughput and order tardiness. The proposed DPCS can be easily implemented as a real-time DPCS due to its simplicity, modularity and the limited information it requires. The proposed adaptive scheme can be integrated in any parametric production control system.