Query: supply chain planning Semiconductor

Candidate papers:

abstract: Part I of this three part series described semiconductor supply chains from the decision making and functional perspectives, using this as a framework to review the industrial engineering (IE) and operations research (OR) literature on the problems arising in these supply chains. Part I then reviewed the literature on Strategic Network Design, Supply Chain Coordination, Sustainability and Semiconductor Supply Chain Simulation, while Part II reviewed Demand Planning, Inventory Management, and Capacity Planning. This paper concludes the series, discussing Master Planning, Production Planning, Demand Fulfilment, and Available to Promise (ATP) in semiconductor supply chains.
author_names: Lars Monch

Reha Uzsoy

John W Fowler
title: A survey of semiconductor supply chain models part III: master planning, production planning, and demand fulfilment
venue: Int. J. Prod. Res.
year: 2018

abstract: Part I of this three part series described semiconductor supply chains from the decision making and functional perspectives, using this as a framework to review the industrial engineering and operations research literature on the problems arising in these supply chains. Part I then reviewed the literature on Strategic Network Design, supply chain coordination, sustainability and simulation based decision support. This paper, Part II, reviews the areas of Demand Planning, Inventory Management and Capacity Planning in semiconductor supply chains. Part III concludes the series by discussing models to support Master Planning, Production Planning and Demand Fulfilment in this industry.
author_names: Reha Uzsoy

John W Fowler

Lars Monch
title: A survey of semiconductor supply chain models Part II: demand planning, inventory management, and capacity planning
venue: Int. J. Prod. Res.
year: 2018

abstract: Abstract Model Based System Engineering (MBSE) is an increasingly important methodology to support system engineering and has attained a high level of attentiveness in business simulation practices as a conceptual modelling approach. In this paper, we present our results related to the application of MBSE approaches in complex semiconductor manufacturing supply chain planning systems. We investigate System Modeling Language (SysML) Web Ontology Language (OWL) and Business Process Modeling Notation (BPMN) as different approaches and languages for MBSE. These approaches are surveyed and used to develop conceptual models for the simulation of the order management process inside the supply chain management. This study aims to survey and offer a number of implications for MBSE practice and seeks to stimulate and guide further research in this area.
author_names: Behrouz Alizadeh Mousavi

Radhia Azzouz

Cathal Heavey

Hans Ehm
title: A Survey of Model Based System Engineering Methods to Analyse Complex Supply Chains: A Case Study in Semiconductor Supply Chain
year: 2019

abstract: Moore's Law indicates that the amount of transistors which can be accommodated on integrated circuit (IC) double every two years in semiconductor manufacturing industry. As a capital intensive and competitive industry, supply chains in the semiconductor industry feature high structural complexity and high demand uncertainty. In order to enhance the effectiveness of the enterprise, total resource management (TRM) for semiconductor industry is increasingly crucial. Past studies focused on measuring the effectiveness of either demand fulfillment or capacity utilization, but little researches have done for investigating the inter coordination on both aspects. This paper proposes overall supply chain effectiveness (OSCE) for the incorporation of demand planning and capacity portfolio based on PDCCCR framework to evaluate the effectiveness of semiconductor supply chain industry. The proposed index is implemented in an empirical study based on a simulation model for semiconductor backend production. Finally, the paper concludes with the discussion of future research directions.
author_names: Hsuan An Kuo

Thomas Ponsignon

Hans Ehm

Chen Fu Chien
title: Overall Supply Chain Effectiveness (OSCE) for Demand and Capacity Incorporation in Semiconductor Supply Chain Industry
venue: 2019 IEEE International Conference on Smart Manufacturing, Industrial Logistics Engineering (SMILE)
year: 2019

abstract: Supply chain collaboration is the prerequisite for successful procurement and operational business practices for short life cycled products, especially due to competitive marketplace, and globalization, which necessitates the requirement of most appropriate planning frameworks. Supply chain planning in the semiconductor industry integrates the complex network of wafer foundries, probe and assembly manufacturing sites together to enhance operational effectiveness. So, the supply chain planning system should aggregate data from multiple sources to provide visibility and interoperable collaboration to an extended network of stakeholders. While exploring buyer supplier collaborative relationships and new procurement opportunities, the present work proposes a framework for depicting an appropriate policy. The following aspects of the supply chain are explored while developing such a framework: (1) business planning, (2) supply management, (3) demand management, (4) multi echelon inventory optimization, (5) customer order fulfillment, and (6) transportation and logistics management. The novelty of this work lies in the simultaneous consideration of six interrelated perspectives of supply chain planning along with the perspective of collaboration among supply chain members on the basis of information sharing. The proposed framework captures the technological and business basis for integration of various elements for supply chain planning with expected outcomes.
author_names: Bikram K Bahinipati
title: A Framework for Semiconductor Industry Supply Chain Planning: The Procurement Perspective
year: 2010

abstract: Abstract Where demand outstrips supply, there will result in shortages to end customers. In such a case decisions need to be made of how to allocate supply to customers. Customer satisfaction requires accurate order promising that leads to better cooperation, as well as trustable orders and forecasts from customers. As a result, customer satisfaction through a trustable promising system leads to more accurate planning for production. In this regard, modern Advanced Planning Systems (APS) provides allocation planning to customers' orders based on "Available To Promise" (ATP) Lack of supply, escalation, and excess demand are propelled by competitive plant capacity, dynamic behaviours of ATP, orders, and demand forecasts in demanding industries like semiconductor manufacturing. When demand exceeds supply, APS needs the support of experts (human intervention) about the time and amount to be allocated to customers. This feature of APS keeps the flexibility of planning to find feasible optimal decisions regarding allocations. In this paper, we propose a mathematical model for the optimization of ATP allocation to customers, where demand exceeds supply, which will be presented as a decision support tool to analyse allocation scenarios. The objective of the proposed mathematical model is maximizing customer service level which is directly related to customer satisfaction while keeping a maximum of stock. The model is being developed from a case study of a European semiconductor supply chain with a sales office in Ireland. In this case study, support will be provided to allocation managers that allows flexibility solutions to be developed. The obtained results have validated the proposed multi objective mathematical model.
author_names: Behrouz Alizadeh Mousavi

Radhia Azzouz

Cathal Heavey
title: MATHEMATICAL MODELLING OF PRODUCTS ALLOCATION TO CUSTOMERS FOR SEMICONDUCTOR SUPPLY CHAIN
year: 2019

abstract: Semiconductor manufacturing is highly complex, invest intensive and constantly changing due to innovation. The semiconductor product market is highly volatile due to short product life cycles with difficult to predict ramps and end of life demands. These challenges are mitigated via flexible production capabilities, e.g. dynamic routing or rescheduling, used by planning systems to transfer volatile demands to well utilized factories. The product structure is one of the keys for enabling the desired result. Product structure representations include linear, tree, and network. In this paper, definitions of several product structure representations are given and hypothesized benefits and drawbacks are discussed. Research questions are posed, current research efforts are introduced, and the hypothesis that a time dependent network tree representation would be beneficial is postulated. The problem statement is explained by a real case merger where risk and opportunities based on the choice of product structure representation were relevant and no final solution was determined.
author_names: Hans Ehm

Cedric Neau

Christian James Martens

Tim Lauer

Thomas Ponsignon

Joaquin Garcia
title: Research Opportunities Regarding Tree and Network Productstructure Representations in a Semiconductor Supply Chain
venue: 2019 Winter Simulation Conference (WSC)
year: 2019

abstract: Semiconductor manufacturing is highly complex, invest intensive and constantly changing due to innovation. The semiconductor product market is highly volatile due to short product life cycles with difficult to predict ramps and end of life demands. These challenges are mitigated via flexible production capabilities, e.g. dynamic routing or rescheduling, used by planning systems to transfer volatile demands to well utilized factories. The product structure is one of the keys for enabling the desired result. Product structure representations include linear, tree, and network. In this paper, definitions of several product structure representations are given and hypothesized benefits and drawbacks are discussed. Research questions are posed, current research efforts are introduced, and the hypothesis that a time dependent network tree representation would be beneficial is postulated. The problem statement is explained by a real case merger where risk and opportunities based on the choice of product structure representation were relevant and no final solution was determined.
author_names: Navonil Mustafee

K -H G Bae

Sanja Lazarova-Molnar

Markus Rabe

C Szabo

Pol-Andre Haas

Y-J Son
title: OPPORTUNITIES REGARDING TREE AND NETWORK PRODUCT STRUCTURE REPRESENTATIONS IN A SEMICONDUCTOR SUPPLY CHAIN
year: 2019

abstract: Supply chain management issues have become increasingly important to the semiconductor industry over the last two decades due to the global distribution of facilities and increasing numbers of firms specialising in particular stages. This series of three papers reviews the literature on modelling and analysis of the larger semiconductor supply chain. After describing the structure of semiconductor supply chains to provide context for the research efforts, we propose a classification scheme for the relevant literature. The remainder of this paper (Part I) then focuses on Strategic Network Design models for this industry, supply chain coordination through contracting and semiconductor supply chain simulation. Part II discusses Demand Planning, Inventory Management and Capacity Planning, while Part III addresses Master Planning, Production Planning and Demand Fulfilment.
author_names: Lars Monch

Reha Uzsoy

John W Fowler
title: A survey of semiconductor supply chain models part I: semiconductor supply chains, strategic network design, and supply chain simulation
venue: Int. J. Prod. Res.
year: 2018

abstract: In this paper, we propose a deterministic mixed integer programming model to schedule weekly production quantities for semiconductor manufacturing in order to meet forecasted demand over a six month planning horizon. The model considers facility capacities, facility qualifying, limits on the number of facilities to use, and unit level minimum inventory requirements. Model validity is demonstrated with a simple test case based on an industry dataset. A case study is then presented using actual industry data. Minimum inventory requirement levels are varied and compared to results obtained from traditional safety stock policies.
author_names: Jonathan J Lowe

Scott J Mason
title: Integrated Semiconductor Supply Chain Production Planning
venue: IEEE Transactions on Semiconductor Manufacturing
year: 2016