The Impact of Flexibility on Engineer-to-Order Production Planning

2021 ◽  
pp. 108183
Author(s):  
Robert Brachmann ◽  
Rainer Kolisch
Keyword(s):  
Production Planning ◽  
Engineer To Order ◽  
The Impact

scholarly journals SUPPORT FOR MANAGING PARTLY CONFIGURABLE MODULAR SYSTEMS

2021 ◽  
Vol 1 ◽  
pp. 2791-2800
Author(s):  
Jarkko Pakkanen ◽  
Teuvo Heikkinen ◽  
Nillo Adlin ◽  
Timo Lehtonen ◽  
Janne Mämmelä ◽  
...  
Keyword(s):  
Portfolio Management ◽  
Product Variety ◽  
Added Value ◽  
Modular System ◽  
Product Management ◽  
Design Decision ◽  
Product Portfolio ◽  
Modular Systems ◽  
Engineer To Order ◽  
The Impact

AbstractThe paper studies what kind of support could be applied to the management of partly configurable modular systems. The main tasks of product management, product portfolio management and product variety management are defined. In addition, a partly configurable product structure and modular system are defined. Because the limited support in the literature for managing partly configurable modular systems, the article reviews previous product development cases in which authors have been involved on lessons learnt basis, i.e., if the methods and tools used in the cases could provide support for the research objective. As a result, the existing definition of the modular system should be extended by the concepts of non-module and design decision sequence description when dealing with partly configurable modular systems. This is because engineer-to-order should be made possible in cases where it brings clear added value to the customer compared to completely pre-defined solutions that may limit the customer's interest in the offering. Tools to assess the impact of changes to the product offering are required. These should be taken into account in frameworks that are used in method and tool development.

An Available-to-Promise System for Network-Manufacturing

2011 ◽  
Vol 268-270 ◽  
pp. 303-308 ◽  
Author(s):  
Wen Hao Wang ◽  
Qiong Zhu ◽  
Jie Zhang
Keyword(s):  
Production Planning ◽  
Planning Horizon ◽  
Global Environment ◽  
Quick Response ◽  
Key Factors ◽  
Planning And Scheduling ◽  
Production Planning And Scheduling ◽  
Analysis Experiment ◽  
Order Promising ◽  
The Impact

This Paper Presents Development of an Available-to-Promise (ATP) System for Network-Manufacturing in a Global Environment where Multi-Plants Are Manufacturing Products Collaboratively and Are Globally Networked. within the Multi-Plant Mode, the ATP Process Is Challenged to Give Not only Quick Response but Also Precise Order Promising by Considering the Coordination of Production Planning and Scheduling among Plants. in this Paper, an Order Decision and Production Planning Integrated ATP Model Was Developed and a Series of Performance Analysis Experiment Was Conducted to Reveal the Impact of some Key Factors such as Planning Horizon, Batch Interval Etc. on Overall Profit.

Environment Pollutant Standard: The Production Planning within Certain Pollution

2013 ◽  
Vol 709 ◽  
pp. 903-906
Author(s):  
Hai Yang Shang
Keyword(s):  
Environmental Pollution ◽  
Production Planning ◽  
Human Life ◽  
Human Society ◽  
Production Output ◽  
The Impact

With the development of human society, modern industrial and human life has caused serious damage on the environment. The paper has introduced the background about environmental pollution affecting the healthy and the development of socioeconomics briefly. Furthermore, a model is employed to describe the production planning within the certain pollution standard. Finally, the results show that the impact of the inducement to pollution on production output is markedly, and SO2 is obviously the COD.

scholarly journals Joint Optimal Production Planning for Complex Supply Chains Constrained by Carbon Emission Abatement Policies

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Longfei He ◽  
Zhaoguang Xu ◽  
Zhanwen Niu
Keyword(s):  
Supply Chains ◽  
Production Planning ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Joint Production ◽  
Optimal Production ◽  
Carbon Emission Reduction ◽  
Regulatory Policies ◽  
Emission Regulation ◽  
The Impact

We focus on the joint production planning of complex supply chains facing stochastic demands and being constrained by carbon emission reduction policies. We pick two typical carbon emission reduction policies to research how emission regulation influences the profit and carbon footprint of a typical supply chain. We use the input-output model to capture the interrelated demand link between an arbitrary pair of two nodes in scenarios without or with carbon emission constraints. We design optimization algorithm to obtain joint optimal production quantities combination for maximizing overall profit under regulatory policies, respectively. Furthermore, numerical studies by featuring exponentially distributed demand compare systemwide performances in various scenarios. We build the “carbon emission elasticity of profit (CEEP)” index as a metric to evaluate the impact of regulatory policies on both chainwide emissions and profit. Our results manifest that by facilitating the mandatory emission cap in proper installation within the network one can balance well effective emission reduction and associated acceptable profit loss. The outcome that CEEP index when implementing Carbon emission tax is elastic implies that the scale of profit loss is greater than that of emission reduction, which shows that this policy is less effective than mandatory cap from industry standpoint at least.

scholarly journals Monte Carlo Simulation and Scenario Analysis Based Limestone Quarry Production Planning

2021 ◽  
Vol 12 (1) ◽  
pp. 41-45
Author(s):  
Kausar Sultan Shah ◽  
Safi Ur Rehman
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Chemical Composition ◽  
Production Planning ◽  
Scenario Analysis ◽  
Raw Materials ◽  
Raw Material ◽  
Mix Design ◽  
Efficient Planning ◽  
The Impact

The key factor behind raw mix design in the cement factory is the appropriate production planning, resulting in high-quality raw material. Quarry managers usually come up with uncertainty-related raw materials due to variations in chemical composition. These uncertainties required efficient planning in terms of useful insight into this problem. This research provides a detailed explanation of scenario analysis of raw materials used in cement manufacturing using Monte Carlo simulation (MCS) and indices. Scenario analysis is used to predict the possibility of best, worst and most likely cases of raw material’s quality. Whereas, Monte Carlo simulation is used to evaluate the inherent uncertainty associated with chemical composition values in order to analyze the impact of truly unpredictable scenarios. The predictive results help in decisions related to production planning, raw mix design optimization and increasing the probability of designing the best plan.

scholarly journals Teaching-Learning Strategies to Production Planning and Control Concepts: Application of Scenarios to Sequencing Production with Virtual Reality Support

2021 ◽  
Vol 20 (8) ◽  
pp. 108-125
Author(s):  
Fernando Elemar Vicente dos Anjos ◽  
Luiz Alberto Oliveira Rocha ◽  
Rodrigo Pacheco ◽  
Débora Oliveira da Silva
Keyword(s):  
Virtual Reality ◽  
Production Planning ◽  
Learning Strategies ◽  
Production Planning And Control ◽  
Production Engineering ◽  
Planning And Control ◽  
Process Manufacturing ◽  
Teaching Learning ◽  
And Control ◽  
The Impact

This paper aims to present scenarios to be applied in higher education to the theme of production planning and control, addressing factors of the production system and indicators arising from this process and the application of virtual reality to support the process. The applied method combines the development of six scenarios for virtual reality application and the discussion about the impacts in indicators from the production planning and control, for example, inventory in the process, manufacturing lead-time, use of equipment, and punctual delivery attendance. Findings revealed that the teaching-learning process of production planning and control, when applied through scenarios, generates opportunities for students to learn the impact in the indicators. The virtual reality in this environment supports creating differentiated teaching-learning environments to generate the most significant knowledge for students which positively impacts the future in the world of work. In addition, it allows people involved in the teaching-learning processes of production engineering to apply the concepts presented in the sequencing process, lean about the impacts of decisions on production sequencing indicators and appreciate the support of virtual reality to generate an environment more cognitive for students.

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