scholarly journals Design Methodology and Tools in Factory of the Future

2021 ◽  
Vol 11 (1) ◽  
pp. 3-37
Author(s):  
Florea Adrian ◽  
Mironescu Ion ◽  
Crăciunean Daniel ◽  
Morariu Daniel ◽  
Volovici Daniel
Keyword(s):  
System Design ◽  
Design Methodology ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Design Method ◽  
Preliminary Design ◽  
Modelling Language ◽  
Manufacturing System Design ◽  
Design Skills ◽  
Factory Of The Future

Abstract This paper presents a design method and tool developed to support the skill forming activities in the DigiFoF network (https://www.digifof.eu/). The focus is on training of manufacturing system design skills both as HEI education and vocational training, but preliminary design of new manufacturing systems is also supported (e.g in the development of small business process scenarios). We proposed a model-based methodology for solving of the manufacturing system design problems The methodology and the supporting tool are centred around a less abstract Domain-Specific Modelling Language (DSML). The language is easy to learn due to its few components. A modelling and simulation environment named Digital Production Planner Tool (DPPT) was generated from the metamodel of the DSML. The degree of abstraction used by this tool corresponds well to the intended use in training and preliminary design. Our method incorporates by design the possibility to impose constraints at the modelling language level to limit the modelling space to feasible/possible solutions. The resulting tool enforces these constraints in the use and supports the development of feasible designs even by inexperienced designers. The access to the conceptual model allows the translation of the model to other modelling language like Petri net. This extends the support for the design methodology. The whitepaper presents a use case for the developed method and tool: the design of a chocolate manufacturing line.

MANUFACTURING SYSTEMS MODELLING USING SYSTEM DYNAMICS: FORMING A DEDICATED MODELLING TOOL

2003 ◽  
Vol 02 (01) ◽  
pp. 71-87 ◽  
Author(s):  
A. OYARBIDE ◽  
T. S. BAINES ◽  
J. M. KAY ◽  
J. LADBROOK
Keyword(s):  
System Dynamics ◽  
System Design ◽  
Discrete Event Simulation ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Computer Modelling ◽  
Discrete Event ◽  
Event Simulation ◽  
Manufacturing System Design ◽  
Computer Based

Discrete event simulation is a popular aid for manufacturing system design; however in application this technique can sometimes be unnecessarily complex. This paper is concerned with applying an alternative technique to manufacturing system design which may well provide an efficient form of rough-cut analysis. This technique is System Dynamics, and the work described in this paper has set about incorporating the principles of this technique into a computer based modelling tool that is tailored to manufacturing system design. This paper is structured to first explore the principles of System Dynamics and how they differ from Discrete Event Simulation. The opportunity for System Dynamics is then explored, and this leads to defining the capabilities that a suitable tool would need. This specification is then transformed into a computer modelling tool, which is then assessed by applying this tool to model an engine production facility.

scholarly journals Extension of Manufacturing System Design Decomposition to Implement Manufacturing Systems That are Sustainable

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
David S. Cochran ◽  
Steve Hendricks ◽  
Jason Barnes ◽  
Zhuming Bi
Keyword(s):  
System Design ◽  
Continuous Improvement ◽  
Systems Engineering ◽  
Design Theory ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Performance Metrics ◽  
Design Decomposition ◽  
Manufacturing System Design ◽  
Axiomatic Design Theory

This paper offers an extension of axiomatic design theory to ensure that leaders, managers, and engineers can sustain manufacturing systems throughout the product lifecycle. The paper has three objectives: to provide a methodology for designing and implementing manufacturing systems to be sustainable in the context of the enterprise, to define the use of performance metrics and investment criteria that sustain manufacturing, and to provide a systems engineering approach that enables continuous improvement (CI) and adaptability to change. The systems engineering methodology developed in this paper seeks to replace the use of the word “lean” to describe the result of manufacturing system design. Current research indicates that within three years of launch, ninety percent of “lean implementations” fail. This paper provides a methodology that leaders, managers, and engineers may use to sustain their manufacturing system design and implementation.

Design for Lean Manufacturing: Incorporating Lean Considerations During Product Development

2006 ◽  
Author(s):  
S. J. Pavnaskar ◽  
D. Weaver ◽  
J. K. Gershenson
Keyword(s):  
System Design ◽  
Continuous Improvement ◽  
Lean Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Manufacturing Operations ◽  
Manufacturing System Design ◽  
Lean Engineering ◽  
Product And Process ◽  
Lean Operations

Lean has become a “must-use” philosophy for businesses today. Lean manufacturing focuses on the elimination of waste in manufacturing operations. Similarly, companies have started using lean engineering to eliminate wastes from their engineering processes. Both lean manufacturing and lean engineering yield dramatic improvements in quality, cost, and delivery. However, the philosophy of lean (manufacturing and engineering) revolves around the continuous improvement of existing processes. Costs associated with continuous improvement can be significantly reduced by incorporating “lean” considerations when designing a product, process, or manufacturing system. This is known as design for lean manufacturing (DfLM). DfLM guides the design of a product, process, or a manufacturing system to enable lean operations when in production, just as design for assembly (DFA) guides the design of a product to allow easier assembly during production. Currently, there are no guidelines that would help a product or process designer in considering to lean operations during design. Note that usage of the word “product” in this paper must be interpreted in a literary sense and not as a “widget.” The “product” of a manufacturing engineering process is a complete manufacturing system. In this paper, we consider manufacturing system design and propose a novel set of structured DfLM guidelines for designing a manufacturing system. These guidelines will be a valuable resource for manufacturing engineers to guide manufacturing system design for new products to enable lean operations once the system is in production. DfLM guidelines for system design also will help plant engineers and rapid continuous improvement managers to assess existing manufacturing systems and identify and prioritize improvement efforts. The proposed DfLM guidelines are then validated for accuracy, completeness, and redundancy by using them to evaluate an existing benchmark manufacturing system. The initial DfLM guidelines show promise for use in designing manufacturing systems that are easy to manage, flexible, safe, build quality into the products, optimize material flow, fully utilize all resources, maximize throughput, and continuously produce what the customer wants just in time. Similar guidelines can be proposed for product and process design to further enhance the efficiency of operations and reduce the overhead of continuous improvement efforts.

Mathematical Models for Manufacturing Systems Capacity Planning and Expansion – An Overview

2015 ◽  
Vol 791 ◽  
pp. 125-131 ◽  
Author(s):  
Arkadiusz Gola ◽  
Marcin Relich ◽  
Grzegorz Kłosowski ◽  
Antoni Świć
Keyword(s):  
Mathematical Models ◽  
System Design ◽  
Capacity Planning ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Optimal Investment ◽  
System Capacity ◽  
Market Demand ◽  
Manufacturing System Design ◽  
Major Decision

When planning a new manufacturing system, the optimal investment in the system capacity is a major decision to make. The problem of capacity planning is not an easy because of the unpredictable character of the market demand and multi-criteria optimization character of the task. Therefore there is still no one complex methodology of the capacity planning and management. In this paper some mathematical models for capacity planning which can be used at the stage of manufacturing system design or expansion are presented.

Sustaining the Competitive Edge of Small to Medium Size Enterprises Through Innovative Manufacturing System Design

2014 ◽  
Author(s):  
Mohamed A. Gadalla
Keyword(s):  
System Design ◽  
Flexible Manufacturing ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Smart Manufacturing ◽  
Medium Size ◽  
Market Conditions ◽  
Competitive Edge ◽  
Manufacturing System Design ◽  
Smart Manufacturing Systems

Increasing Small to Medium size Enterprises (SME’s) competitive edge requires continuously developing creative and novel methods and solutions. This paper presents a novel design for a manufacturing system named Smart Manufacturing Systems (SMS). The new design can be viewed as a modification to the Flexible Manufacturing System (FMS) to better suits continuously changing market conditions, which may lead a company to develop a more sustainable competitive edge. The new design address several issues in manufacturing system design that affect the competitiveness of the system such as: merger of different manufacturing processes, non-productive times, and to be able to performing economically under different market conditions.

scholarly journals Sustainable Reconfigurable Manufacturing System Design Using Adapted Multi-Objective Evolutionary Based Approaches

2021 ◽  
Author(s):  
Imen Khettabi ◽  
Lyes Benyoucef ◽  
Mohamed Amine Boutiche
Keyword(s):  
Genetic Algorithms ◽  
System Design ◽  
Manufacturing Systems ◽  
Manufacturing System ◽  
Total Production ◽  
Reconfigurable Manufacturing ◽  
Reconfigurable Manufacturing System ◽  
Nsga Ii ◽  
Multi Objective ◽  
Manufacturing System Design

Abstract Nowadays, manufacturing systems should be cost-effective and environmentally harmless to cope with various challenges in today's competitive markets. In this paper, we aim to solve an environmental oriented multi-objective reconfigurable manufacturing system design (ie., sustainable reconfigurable machines and tools selection) in the case of a single unit process plan generation. A non-linear multi-objective integer program (NL-MOIP) is presented first, where four objectives are minimised respectively, the total production cost, the total production time, the amount of the greenhouse gases emitted by machines and the hazardous liquid wastes. Second, to solve the problem, we propose four adapted versions of evolutionary approaches, namely two versions of the well known non-dominated sorting genetic algorithm (NSGA-II and NSGA-III), weighted genetic algorithms (WGA) and random weighted genetic algorithms (RWGA). To illustrate the efficiency of the four approaches, several instances of the problem are experimented and the obtained results are analysed using three metrics respectively hypervolume, spacing metric and cardinality of the mixed Pareto fronts. Moreover, the influences of the probabilities of genetic operators on the convergence of the adapted NSGA-III are analysed and TOPSIS method is used to help the decision maker ranking and selecting the best process plans.

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