Real Manufacturing System Research Articles

A two-stage adaptive fruit fly optimization algorithm for unrelated parallel machine scheduling problem with additional resource constraints

In this paper, an unrelated parallel machine scheduling problem with additional resource constraints (UPMSP_RC) from the real world manufacturing systems is studied. With the objective of minimizing the makespan, a mixed integer linear programming model is presented and several properties are analyzed. Furthermore, a two-stage adaptive fruit fly optimization algorithm (TAFOA) is proposed to solve the UPMSP_RC. At the first stage, a heuristic is proposed to generate an initial solution with high quality. At the second stage, the initial solution is adopted as the initial swarm center for further evolution. During the evolution, the search manners are selected adaptively with the guidance of the problem-specific knowledge, which is a sufficient condition of the best schedule under a given job-to-machine assignment. Moreover, the effect of parameters on the performance of the TAFOA is investigated by using the two-factor analysis of variance (ANOVA). Finally, extensive numerical comparisons are carried out to show the effectiveness of the TAFOA in solving the UPMSP_RC.

A switching mechanism framework for optimal coupling of predictive scheduling and reactive control in manufacturing hybrid control architectures

Nowadays, manufacturing systems are seeking control architectures that offer efficient production performance and reactivity to disruptive events. Dynamic hybrid control architectures are a promising approach as they are not only able to switch dynamically between hierarchical, heterarchical and semi-heterarchical structures, they can also switch the level of coupling between predictive scheduling and reactive control techniques. However, few approaches address an efficient switching process in terms of structure and coupling. This paper presents a switching mechanism framework in dynamic hybrid control architectures, which exploits the advantages of hierarchical manufacturing scheduling systems and heterarchical manufacturing execution systems, and also mitigates the respective reactivity and optimality drawbacks. The main feature in this framework is that it monitors the system dynamics online and shifts between different operating modes to attain the most suitable production control strategy. The experiments were carried out in an emulation of a real manufacturing system to illustrate the benefits of including a switching mechanism in simulated scenarios. The results show that the switching mechanism improves response to disruptions in a global performance indicator as it permits to select the best alternative from several operating modes.

Application of MCDM-Based TOPSIS Method for the Optimization of Multi Quality Characteristics of Modern Manufacturing Processes

Optimization of non-conventional machining (NCM) processes viz. AJM, AWJM, EDM, WEDM, ECM, ECMM, LBM, PAC, etc. has always been an open research area for researchers. In recent manufacturing environment, almost all the NCM processes consist of a number of input and output to be considered together. The purpose of the present article is to highlight the application of a multi-criteria decision making (MCDM) based method called Technique of Order Preference by Similarity of Ideal Solution (TOPSIS) in optimization of some modern manufacturing processes (MMPs). In the present paper, seven different MMPs namely Electro Chemical Honing (ECH), Abrasive Water Jet Machining (AWJM), Abrasive Jet Machining (AJM), Laser Beam Machining (LBM), Plasma Arc Cutting (PAC), Laser Cutting (LC) and Electric Discharge Machining (EDM) were exemplified. The multiple outcomes of all the illustrated MMPs have been optimized simultaneously by using TOPSIS method. It is a simple, systematic, and logical technique which can be employed to obtain the best parametric combination of cutting parameters. It was observed that the results attained by using TOPSIS method were almost tie with those derived by past researchers. This proves the applicability and adaptability of the TOPSIS method while solving different MCDM-based problems in a real manufacturing system.

Minimizing the makespan for a serial-batching scheduling problem with arbitrary machine breakdown and dynamic job arrival

Many dynamic events exist in real manufacturing systems, such as arbitrary machine breakdowns and dynamic job arrivals, which makes the scheduling problem even more complicated. In this paper, we address a serial-batching scheduling problem with the above dynamic events. Jobs need to be processed on the serial-batching machines of two manufacturers and then transported by vehicles to a customer for further processing. The objective of the scheduling problem is to minimize the makespan, and the problem is proved to be strongly NP-hard. Some structural properties and a lower bound of the problem are also proved or derived. On the basis of job arrival times, we divide the problem into two phases and propose different rules regarding these two phases. Based on these properties and rules, a heuristic algorithm is developed to solve the problem and its worst case performance is analyzed. The heuristic algorithm is tested on a large set of randomly generated problem instances, and the relative gaps between the found lower bound and the solutions of the proposed heuristic algorithm are reported. The experimental results illustrate the high efficiency and effectiveness of the proposed heuristic algorithm compared with other four classic approaches.

Robust deadlock control for automated manufacturing systems with an unreliable resource

So far, most of deadlock control policies are proposed based on the assumption that automated manufacturing systems (AMSs) have no unreliable resources. While in real manufacturing systems, resource failure is inevitable and will reduce the number of available resources. This paper focuses on the robust deadlock control problem for AMSs with an unreliable resource. Petri nets are used to model the unreliable systems, and a subclass of the ordinary and conservative Petri nets, known as system of simple sequential process with resources (S3PR), is studied. A resource failure and recovery net is added to describe the resource failure and recovery. To prevent each siphon from being emptied, the concept of constraint set for a strict minimal siphon is introduced. By limiting the number of tokens in each constraint set, a robust deadlock controller is devised. It is proved that our controller can guarantee the liveness of the controlled system no matter one resource fails or not. Finally, some examples are provided to illustrate the validity of the proposed robust deadlock controller.

The elementary flux modes of a manufacturing system: a novel approach to explore the relationship of network structure and function

Elementary flux modes (EFMs) are a concept from Systems Biology, where they serve as an indicator of component relevance in metabolic networks. An elementary flux mode is a functionally relevant, non-decomposable path through a given network. In this paper, we apply elementary flux mode analysis to manufacturing systems, with the aim of using the number of EFMs as a predictor for resource significance in the manufacturing system. For this, we formulate a network representation of a manufacturing process, which allows us to define the manufacturing equivalent of a stoichiometric matrix to draw an analogy between metabolic and manufacturing systems. This, in turn, allows the computation of EFMs, which we conduct in a case-study for a real manufacturing system. We further show that the change of EFMs under resource breakdown is a good indicator of the average order lateness in the manufacturing system. In this way, EFMs provide insight into the relationship of network structure and function in manufacturing.

The Graph of Operations Planning Sequence of a Production Order for Scheduling with Mixed Planning Strategies and Alternatives

The paper presents the most important issues related to the scheduling of production orders in real manufacturing systems. In the elaborated method an and/or type graph of operations planning sequence of a production order is proposed for modelling the production system load. In a single structure the graph takes into account alternative routes of a production order realisation and the precedence constraints in presence of complex, hierarchical structures of processes. Two modelling ways of that process using the "operation on the edge" or "operation on the node" notation are also presented. In the developed method scheduling strategies, which have a major impact on the order of placing operations in the schedule and handling of production lots are also considered. By a state space graph representation of scheduling problem, using graph theory, it can be possible to analyze the structure and complexity of both the modelling problem and the graph search techniques.

Scheduling Schemes Based on Searching the Aggregated Graph of Operations Planning Sequence

The searching state space in scheduling of real manufacturing systems with discrete and multi-assortment production is discussed in this paper. The production load is represented by a directed and/or graph called “the aggregated graph of operations planning of the set of orders”. It determines the order of operations, according to which they will be inserted into a schedule. This order must always comply with all assumed precedence and resource constraints and also with given scheduling strategy of a production order. In the elaborated representation the complex products structures and alternative routes of their realization are also considered. The most important issues related to searching this space are discussed in this paper. These include: a general method for searching the graph, sequencing of parallel processes and operations using schedule generation schemes and selection of routes variants.

Procjena praktične primjene simulacije postrojenja u obliku eksperimenata

This contribution deals with the Simulation of manufacturing systems. Plant simulation is a modern instrument for optimizing factory production; however, the initial investment is high, especially for human resources, since the creation of a simulation model requires a lot of data from manufacturing, which needs to be analyzed and used as input into the simulation so that the simulation model is as close as possible to the real manufacturing system. Simulation enables changes to first be carried out in the simulation model and the defining of possible problems, through which in this case it is possible to avoid when introducing changes into an operation. The measure of effectiveness of using inputs is the productivity of a manufacturing system, and the aim of organization management is to monitor, analyze and improve a manufacturing system through optimizing for the purpose of increasing its efficiency, ensuring higher quality and a higher volume of production, shortening supply time in the scope of transportation, improving logistics and increasing the profitability of the given organization.

Development of Rescheduling Framework to Overcome the Different Source of the Disruptions in the make to Order Supply Chain with the Reverse Flow of after-sales Service

Supply chain management is a stratagem, which produces the product with right quality, appropriate quantity, in right time and it deliver the exact order quantity to the right person. However, the uncertainty in the real time manufacturing system is unavoidable. Handling of the post disruption and selecting the suitable rescheduling strategies to overcome the disruption are challengeable task. The current paper deals the framework development to manage disruption from the various entities in the house hold goods manufacturing system. Machine breaks down, supply delay, entry of returned goods, rush orders, supply failure, order postponement, order preponement, order cancellation and the entry of the rework are considered as disruption. The objective of the frame work is to meet the delivery schedule under disruption. Key performance indicator for each disruption and monitoring them from each entities are discussed. This systematic frame work escorts to conduct case study by incorporating popular rescheduling strategies.

Simulation-based Performance Improvement Towards Mass Customization in Make to Order Repetitive Company

The diversity of customers needs and wants leads the manufacture to be agile. The products must be high customized products and very close to the customers’ expectations. In order-based manufacturing environment such as Make to Order (MTO) company, production activity could be started only after the orders were received. However, naturally, customers don’t want to wait for long time, hence, short lead time is a must besides high customization. Such situation forces the company to combine the concept of order-based and stock-based manufacturing. This study presents the design of manufacturing that has high flexibility to produce many type of products with short manufacturing lead time using Mass Customization (MC) concept. Improvement of the manufacturing system is carried out through the definition of Customer Order Decoupling Point (CODP). The manufacturing design and analysis is conducted using simulation approach while the case study is taken from real manufacturing system which is a furniture company in Indonesia. Result of this study shows that the proposed manufacturing design could reduce the manufacturing lead time from 43 days to 24 days or about 44.19% when producing 15 types of product with varying demand.

Analysis of competitiveness level in an industrial company using a continuous improvement-based approach

In recent years, companies have emerged in an advanced competitive environment. To meet the requirements of cost reduction, customer demand, minimising delays, quality and variety improvement, companies must improve their performance to remain competitive, survive and expand. To achieve this goal, several models are used such as total quality management, Kaizen, just in time, enterprise resource planning, business process reengineering and Six Sigma, etc. In this work, we look for an effective model (drawn from Six Sigma approach) used mainly to warrant the competitiveness of a company denoted as the weighted defects per million opportunities model. The aim of this paper is to apply this model to measure process levels (weights) and assess the company competitiveness. The results of this model are applied in a real manufacturing system which produces gas bottles.

Lead-time oriented production control policies in two-machine production lines

The ability of meeting the target production lead times is of fundamental importance in modern manufacturing systems producing perishable products, where the product quality or value deteriorates with the time parts spend in the system, and in manufacturing contexts where strict lead time constraints are imposed due to tight shipping schedules. In these settings, traditional manufacturing system engineering methods and token-based production control policies loose effectiveness as they aim at achieving target production rates while minimizing the inventory, without directly taking into account the effect on the lead time distribution. In this paper a production control policy for unreliable manufacturing systems that aims at maximizing the throughput of parts that respect a given lead time constraint is proposed for the First time. The proposed policy jointly considers the actual level of the buffer and the state of the second machine in the system and stops the part loading at the first machine if there is unacceptable risk of exceeding the lead-time constraint. The effectiveness of this new policy against the traditional Kanban policy is quantified by numerical analysis. The results show that this new policy outperforms the Kanban policy by providing a tighter control on the production lead time. This approach paves the way to the introduction of new lead-time oriented production control policies to maximize the effective throughput in real manufacturing systems.

A method for automation software design of mechatronic systems in manufacturing

The fast globalization process of the last decade required companies to optimize internal processes. Additionally, customers requirements are becoming more and more specific, requiring strong customization. In the mechatronic field, the automation software development takes a wide percentage of the overall designing time, due to the lack of structured design processes (specially for small systems) and code reuse.This paper aims to define a first structured approach for the automation software development of small manufacturing systems. The proposed solution is based on concepts like modularization and encapsulation, trying to build a one-to-one relationship between the physical mechatronic object and its control software module. Each module embeds the control software and other information related to the HMI, the documentation and the risk assessment.The introduced method has been implemented on a real small manufacturing system (an industrial manipulator). The components that form the device have been identified and implemented as modules. The design phase becomes, then, a drag and drop composition of such modules, controlled by a state machine that describes the working cycle of the device.

Digital Factory Approach for Flexible and Efficient Manufacturing Systems in the Aerospace Industry

This paper is focused on the employment of Digital Factory methodologies with the aim of improving the flexibility and the efficiency of a real manufacturing cell dedicated to the precision manufacturing of mechanical components for the aerospace industry. An automation upgrade of the cell is proposed, involving the introduction of an industrial robot for part handling, loading and unloading, and a new automatic surface inspection system (ASIS) for the final part inspection. The research activities are carried out within one of the projects of the Italian National Technology Cluster on Intelligent Factory. In this framework, the digital validation of the real manufacturing system is performed through Discrete Event Simulation to analyze the performance of the manufacturing system in terms of productivity and utilization of resources under different alternative scenarios, avoiding the risks associated with physical experimentation on the real system.

Production quality performance in manufacturing systems processing deteriorating products

In several manufacturing contexts including food industry, semiconductor manufacturing, and polymers forming, the product quality deteriorates during production by prolonged exposure to the air caused by excessive lead times. Buffers increase the system throughput while also increasing the production lead time, consequently affecting the product quality. This paper proposes a theory and methodology to predict the lead time distribution in multi-stage manufacturing systems with unreliable machines. The method allows to optimally set inventory levels to achieve target production quality performance in these systems. The industrial benefits are demonstrated in a real manufacturing system producing micro-catheters for medical applications.

Optimisation of the reverse scheduling problem by a modified genetic algorithm

Traditional scheduling methods can only arrange the operations on corresponding machines with appropriate sequences under pre-defined environments. This means that traditional scheduling methods require that all parameters to be determined before scheduling. However, real manufacturing systems often encounter many uncertain events. These will change the status of manufacturing systems. These may cause the original schedule to no longer be optimal or even to be infeasible. Traditional scheduling methods, however, cannot cope with these cases. New scheduling methods are needed. Among these new methods, one method ‘reverse scheduling’ has attracted more and more attentions. This paper focuses on the single-machine reverse scheduling problem and designs a modified genetic algorithm with a local search (MLGA) to solve it. To improve the performance of MLGA, efficient encoding, offspring update mechanism and a local search have been employed and developed. To verify the feasibility and effectiveness of the proposed MLGA, 27 instances have been conducted and results have been compared with existing methods. The results show that the MLGA has achieved satisfactory improvement. This approach also has been applied to solve a real-world scheduling problem from one shipbuilding industry. The results show that the MLGA can bring some benefits.

The Procedure of Reaction to Unexpected Events in Scheduling of Manufacturing Systems with Discrete Production Flow

Rescheduling, as a process of updating the production schedule is a very important element of production planning and control. The occurrence of events that outdate existing schedule is a typical situation in real manufacturing systems. Correct reaction to them allows maintaining the continuity of production and the value of evaluation indicators at the satisfactory level. The paper presents the general rescheduling procedure including activities taken from the occurrence of a disturbance up to introduction of the revised schedule. The procedure includes following steps: registering and identification of the event parameters, decision-making steps about the need and time for schedule correction, steps of changing the scheduling model, selection of rescheduling method, selection of a set of operations to rescheduling and also steps of the creation, selection, and implementation of the new schedule .

A production scheduling simulation model for improving production efficiency

AbstractA real manufacturing system of an electronic company was mimicked by using a simulation model. The effects of dispatching rules and resources allocations on performance measures were explored. The results indicated that the dispatching rules of shortest processing time (SPT) and earliest due date are superior to the current rule of first in first out adopted by the company. A new combined rule, the smallest quotient of dividing shortest remaining processing time (SRPT) by SPT (SRPT/SPT_Min), has been proposed and demonstrated the best performance on mean tardiness time under the current resources situation. The results also showed that using fewer resources can increase their utilization, but it increases the risk of delivery tardiness as well, which in turn will damage the organization’s reputation in the long run. Some suggestions for future work were presented.

Deteriorating job scheduling problem in a job-shop manufacturing system by multi-agent system

The scheduling problem is typically investigated in the literature considering the job-processing times fixed and constant values. In real manufacturing systems, the job-processing times can change due to several factors such as machine and cutting tool deterioration and maintenance issues. This article studies the integration of the deteriorating processing time problem in a multi-agent architecture that supports the scheduling activities in a job-shop manufacturing system. The main problem addressed in this research concerns the policy to restore the workstations to their initial state. It is observed that the state of the workstations and the performance measures of the manufacturing system enables the decision of when to perform the restore activity. It is proposed a policy based on a variable threshold level to decide on the restoration of the workstations. A simulation environment is developed to test the proposed approach to investigate several performance measures. The simulation results highlight how the proposed policy allows to keep a high level of performance reducing the number of restore activities.