scholarly journals New models and algorithms to solve integrated problems of production planning and control taking into account worker skills in flexible manufacturing systems

2021 ◽  
Vol 12 (4) ◽  
pp. 381-400 ◽  
Author(s):  
Norbert Tóth ◽  
Gyula Kulcsár

The paradigm of the cyber-physical manufacturing system is playing an increasingly important role in the development of production systems and management of manufacturing processes. This paper presents an optimization model for solving an integrated problem of production planning and manufacturing control. The goal is to create detailed production plans for a complex manufacturing system and to control the skilled manual workers. The detailed optimization model of the problem and the developed approach and algorithms are described in detail. To consider the impact of human workers performing the manufacturing primary operations, we elaborated an extended simulation-based procedure and new multi-criteria control algorithms that can manage varying availability constraints of parallel workstations, worker-dependent processing times, different product types and process plans. The effectiveness of the proposed algorithms is demonstrated by numerical results based on a case study.

Author(s):  
Abdul Salam Khan ◽  
Khawer Naeem ◽  
Raza Ullah Khan

An abrupt change requires a robust and flexible response from a manufacturing system. Dedicated Manufacturing System (DMS) has been a long practiced taxonomy for mass production and minimum varieties. In contrast, Flexible Manufacturing System (FMS) has been introduced for responding to quantity as well as variety issues. This study considers both production taxonomics by using a multi objective model of cost and time. An Integer Linear Programming (ILP) formulation is presented and subsequently validated. The analysis procedure is administered in two phases. In the first phase, comparison of production cost and process time in DMS and FMS is presented. The model is implemented by using an exact solution approach and results show that FMS is a viable option, compared to DMS, according to the criteria of cost, time, and productivity. In the second phase, sensitivity analysis is performed by using several FMS (n) and the impact of cells selection on the performance of system is studied. It is concluded that n=1 (single cell-based FMS) is more relevant for cost minimization; however, n = 6 is a suitable candidate for producing more quantity in given time horizon (process time minimization). Lastly, key findings are reported, and future research avenues are provided.


2013 ◽  
Vol 378 ◽  
pp. 367-374 ◽  
Author(s):  
Andrey A. Kutin ◽  
Mikhail Turkin

This paper introduces an analytical method for evaluating the performance of closed loop manufacturing systems with unreliable machines and finite buffers. The method involves transforming an arbitrary loop into one without thresholds and then evaluating the transformed loop using a new set of decomposition equations. It is more accurate than existing methods and is effective for a wider range of cases. The convergence reliability, and speed of the method are also discussed. In addition, observations are made on the behavior of closed loop production systems under various conditions. Finally, the method is used in a case study to design a flexible manufacturing system for production of aerospace parts.


2013 ◽  
Vol 404 ◽  
pp. 631-634 ◽  
Author(s):  
Lehel Csokmai ◽  
Ovidiu Moldovan ◽  
Ioan Constantin Tarca ◽  
Radu Tarca

Production systems must be flexible and endowed with techniques and tools allowing an automatic recovery of errors. And so, the subject of error recovery in flexible manufacturing system is always an open issue. The objective of this work consists in proposing a new type of software framework for error troubleshooting in a flexible manufacturing system that is perceived as an Intelligent Space (iSpace). Our framework system is designed to solve the failures in the functioning of the FMS and to generate self-training from previous experience.


Author(s):  
Elvis Hozdić

The objective of this research is to develop a new ontology-based approach for the management and control of cyber-physical production systems (CPPSs). In the CPPSs, the management and control functions are integrated with a physical part of manufacturing system. The function of production planning and control of manufacturing systems (PPC) is an important part of the management and control of the CPPSs. The elements of the cyber system structure enable the dynamic management and control of manufacturing systems in real time, through the realization of the digitalized and cybernated functions of PPC. The proposed approach to management and control of the CPPSs is based on the foundational ontology of manufacturing systems. The digitalized production planning, scheduling, and control functions are implemented as a multi-agent system (MAS). The communication between agents was addressed to support the autonomic decision for each individual agent. A case study demonstrates feasibility of the approach through the use of simulation experiments.


2007 ◽  
Vol 2007 ◽  
pp. 1-24 ◽  
Author(s):  
Jingshan Li ◽  
Ningjian Huang

The flexible manufacturing system (FMS) has attracted substantial amount of research effort during the last twenty years. Most of the studies address the issues of flexibility, productivity, cost, and so forth. The impact of flexible lines on product quality is less studied. This paper intends to address this issue by applying a Markov model to evaluate quality performance of a flexible manufacturing system. Closed expressions to calculate good part probability are derived and discussions to maintain high product quality are carried out. An example of flexible fixture in machining system is provided to illustrate the applicability of the method. The results of this study suggest a possible approach to investigate the impact of flexibility on product quality and, finally, with extensions and enrichment of the model, may lead to provide production engineers and managers a better understanding of the quality implications and to summarize some general guidelines of operation management in flexible manufacturing systems.


2018 ◽  
Vol 35 (01) ◽  
pp. 1850005 ◽  
Author(s):  
James T. Lin ◽  
Chun-Chih Chiu ◽  
Edward Huang ◽  
Hung-Ming Chen

Driven by sensor technologies and Internet of Things, massive real-time data from highly interconnected devices are available, which enables the improvement of decision-making quality. Scheduling of such production systems can be challenging as it must incorporate the latest data and be able to re-plan quickly. In this research, a multi-fidelity model for simultaneous scheduling problem of machines and vehicles at flexible manufacturing system has been proposed. In order to improve the computational efficiency, we extend the framework, called multi-fidelity optimization with ordinal transformation and optimal sampling, with combining with the K-means method. The proposed framework enables the benefits of both fast and inexpensive low-fidelity models with accurate but more expensive high-fidelity models. Results show that this approach can significantly decrease computational cost compared with other algorithms in the literature.


2019 ◽  
Vol 957 ◽  
pp. 195-202 ◽  
Author(s):  
Elizaveta Gromova

With the onset of the Fourth Industrial Revolution, the business environment becomes inherent in changes that occur with maximum speed, as well as characterized by the systemic nature of the consequences. One of them is the transformation of operational management models in industrial enterprises. The modern manufacturing system should focus not only on speed of response and flexibility, but also on the cost and quality of products. Integration of effective models: agile manufacturing, quick response manufacturing and lean production, in order to extract the best from them is proposed. The purpose of this study is to analyze this flexible manufacturing system and to relate it to the current state of the Russian industrial development. Theoretical and practical aspects of this model are presented. The examples of the flexible models introduction in the Russian industrial sector is allocated. The conclusion about the necessity of the flexible manufacturing systems implementation for the Russian industrial development is drawn.


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