scholarly journals Supply Chain Inventories of Engineered Shipping Containers

2016 ◽  
Vol 2016 ◽  
pp. 1-8
Author(s):  
David A. Field ◽  
Dennis E. Blumenfeld
Keyword(s):  
Supply Chain ◽  
Mathematical Models ◽  
Daily Production ◽  
Safety Stock ◽  
Manufacturing Operations ◽  
Damage Repair ◽  
Shipping Containers ◽  
Basic Parameters ◽  
Assembly Operations

Manufacturing operations that assemble parts often receive components in expensive highly engineered shipping containers. As these containers circulate among suppliers, assembly operations, and logistic providers, they require inspections and repairs. This paper presents mathematical models that predict the number of available containers as functions of damage, repair times, and scheduled daily production. The models allow making complex decisions with a few basic parameters. Results not only show a minimal investment in the number of containers and safety stock but also quantify the dependence on damage rates and repair times for ordering additional containers.

scholarly journals Postponement Application in the Fast Fashion Supply Chain: A Review

2017 ◽  
Vol 12 (7) ◽  
pp. 115 ◽  
Author(s):  
MdAfzalul Aftab ◽  
Qin Yuanjian ◽  
Nadia Kabir
Keyword(s):  
Supply Chain ◽  
Value Chain ◽  
Building Blocks ◽  
Inventory Level ◽  
Successful Implementation ◽  
Process Standardization ◽  
Fast Fashion ◽  
Supply Chain Strategy ◽  
Manufacturing Operations ◽  
Inventory Holding

The successful implementation of push-pull supply chain management strategy has an important role in improving the competitiveness of an organization. The objective of a push-pull strategy is to minimize the holding of inventory level in finished form and rather produce finished goods from semi-finished inventory only upon receiving final order. One of the vital building blocks of push-pull supply chain strategy is postponement. The main objective of this review paper is to discuss the concept of postponement and its sub-categories such as product postponement and process postponement and their benefits. Then it is investigated how two prominent fast fashion retailers who are also categorized as original brand manufacturers in the apparel value chain apply the two variants of process postponement e.g. process standardization and process re-sequencing in their manufacturing operations to activate push pull supply chain strategy. The push-pull supply chain strategy in turn helps to reduce their order-to-delivery lead time to stores, reduce inventory holding level and minimize both physical costs and market mediation costs. The paper ends with concluding remarks. A framework is developed to illustrate the push-pull supply mechanism. This paper is a useful resource for practitioners in apparel supply chain willing to remove inefficiencies, costs and risks in their operations.

scholarly journals Uncertainty Simulation of Wood Chipping Operation for Bioenergy Based on Queuing Theory

Forests ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 822
Author(s):  
Yoshida ◽  
Takata
Keyword(s):  
Supply Chain ◽  
Moisture Content ◽  
Queuing Theory ◽  
Wood Chip ◽  
Stochastic Modelling ◽  
Simulation Method ◽  
Daily Production ◽  
Deterministic Simulation ◽  
Loss Compensation ◽  
Truck Arrival

Managing uncertainty is the way to secure stability of the supply chain. Uncertainty within chipping operation and chip transportation causes production loss. In the wood chip supply chain for bioenergy, operational uncertainty mainly appears in the moisture content of the material, chipping productivity, and the interval of truck arrival. This study theoretically quantified the loss in wood chip production by applying queuing theory and stochastic modelling. As well as the loss in production, the inefficiency was identified as the idling time of chipper and the queuing time of trucks. The aim of this study is to quantify the influence of three uncertainties on wood chip production. This study simulated the daily chip production using a mobile chipper by applying queuing theory and stochastic modelling of three uncertainties. The result was compared with the result of deterministic simulation which did not consider uncertainty. Uncertainty reduced the production by 14% to 27% compared to the production of deterministic simulation. There were trucks scheduled but not used. The cases using small trucks show the largest daily production amount, but their lead time was the longest. The large truck was sensitive to the moisture content of material because of the balance between payload and volumetric capacity. This simulation method can present a possible loss in production amount and enables to evaluate some ways for the loss compensation quantitatively such as outsourcing or storing buffer. For further development, the data about the interval of truck arrival should be collected from fields and analyzed. We must include the other uncertainties causing technical and operator delays.

scholarly journals Evaluation of Mathematical Models in Sustainable Supply Chain Management: Gap Analysis

2021 ◽  
Vol 14 (10) ◽  
pp. 25
Author(s):  
Zahra Ghorbani Ravand ◽  
Qi Xu
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Mathematical Models ◽  
Peer Review ◽  
Coal Industry ◽  
Current Situation ◽  
Sustainable Supply Chain ◽  
Context Analysis ◽  
Chain Management ◽  
Sustainable Supply Chain Management

The main purpose of this paper is to present a comprehensive view of the application mathematical models in the designing and implementing SSCM beside to solving problems and making decision.  The research questions are: what kind of mathematical models are used for designing and implementing sustainable supply chain management, how to use them, which industries implemented in, what modules of SSCM depth in and finally finding the gaps between the goals of Sustainable development and current researches and suggestions for further researches. The methodology of the research is Systematic Literature review and evaluation peer review papers which are published in high ranking journals: First, we gather all papers through scientific data bases like Scopus, science direct, MDPI, Springer, Google Scholar. Then, screening papers based on the criteria such as object of paper, subject of paper, journals impact factor, peer review paper, and relative content of the papers. Finally, we selected 245 papers through three steps screening from 2806 papers that they have enough quality and relative to our research goals for context analysis. For context analysis: First we categorize the information of the papers and draw the current situation of researches in the framework of our topic. Then, we evaluate and compare the goals of sustainability and current situation and find the gapes, then, offer suggestions required researches for pollutant industries such as Casting Industry, Heavy Industry, Coal Industry and so on. On the other hand, there are gaps in researches in some modules of SSCM such as packaging, designing products, etc.    

Inventory policies and safety stock optimization for supply chain planning

AIChE Journal ◽  
2018 ◽  
Vol 65 (1) ◽  
pp. 99-112 ◽  
Author(s):  
Braulio Brunaud ◽  
José M. Laínez-Aguirre ◽  
Jose M. Pinto ◽  
Ignacio E. Grossmann
Keyword(s):  
Supply Chain ◽  
Supply Chain Planning ◽  
Inventory Policies ◽  
Safety Stock

A Machine Learning-Based System for Predicting Service-Level Failures in Supply Chains

2021 ◽  
Author(s):  
Gabrielle Gauthier Melançon ◽  
Philippe Grangier ◽  
Eric Prescott-Gagnon ◽  
Emmanuel Sabourin ◽  
Louis-Martin Rousseau
Keyword(s):  
Machine Learning ◽  
Supply Chain ◽  
Service Level ◽  
Learning System ◽  
Safety Stock ◽  
Service Levels ◽  
Sources Of Uncertainty ◽  
Supply Chain Efficiency ◽  
Percentage Points ◽  
Different Sources

Despite advanced supply chain planning and execution systems, manufacturers and distributors tend to observe service levels below their targets, owing to different sources of uncertainty and risks. These risks, such as drastic changes in demand, machine failures, or systems not properly configured, can lead to planning or execution issues in the supply chain. It is too expensive to have planners continually track all situations at a granular level to ensure that no deviations or configuration problems occur. We present a machine learning system that predicts service-level failures a few weeks in advance and alerts the planners. The system includes a user interface that explains the alerts and helps to identify failure fixes. We conducted this research in cooperation with Michelin. Through experiments carried out over the course of four phases, we confirmed that machine learning can help predict service-level failures. In our last experiment, planners were able to use these predictions to make adjustments on tires for which failures were predicted, resulting in an improvement in the service level of 10 percentage points. Additionally, the system enabled planners to identify recurrent issues in their supply chain, such as safety-stock computation problems, impacting the overall supply chain efficiency. The proposed system showcases the importance of reducing the silos in supply chain management.

Towards Implementing a Collaborative Manufacturing Cloud Platform: Experimenting Testbeds Aiming Asset Efficiency

2020 ◽  
Author(s):  
Nuno Santos ◽  
Paula Monteiro ◽  
Francisco Morais ◽  
Jaime Pereira ◽  
Daniel Dias ◽  
...  
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Proof Of Concept ◽  
Cloud Platform ◽  
Industrial Internet Of Things ◽  
Manufacturing Environment ◽  
Collaborative Manufacturing ◽  
Manufacturing Operations ◽  
Industrial Internet ◽  
The Future

Abstract Developing Industrial Internet of Things (IIoT) systems requires addressing challenges that range from acquiring data at the level of the shopfloor, integrated at the edge level and managing it at the cloud level. Managing manufacturing operations at the cloud level arose the opportunity for extending decisions to entities of the supply chain in a collaborative way. Not only it has arisen many challenges due to several interoperability needs; but also in properly defining an effective way to take advantage of the available data, leading to Industrial Digital Thread (IDT) and Asset Efficiency (AE) implementing. This paper discusses implementation concerns for a collaborative manufacturing environment in an IIoT system in order to monitor equipment’s AE. Each concern was addressed in a separate proof of concept testbed. The demonstration is based in a project for the IIoT domain called PRODUTECH-SIF (Solutions for the Industry of the Future).

Beyond COVID-19 supply chain heroism, no dust settling yet – lessons learned at Rolls Royce about advancing risk management thinking

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Remko van Hoek ◽  
David Loseby
Keyword(s):  
Risk Management ◽  
Supply Chain ◽  
Lessons Learned ◽  
First Year ◽  
Multiple Time ◽  
Content Type ◽  
Manufacturing Operations ◽  
Time Horizons ◽  
Management Literature ◽  
The Impact

PurposeWhile there is a rich body of risk management literature and while there have been valuable theoretical advancements on the specific impact of the COVID-19 pandemic on risks, this paper aims to posit that at least four more advancements are needed.Design/methodology/approachThe co-author from Rolls Royce (RR) illustrates the risks experienced and risk management approaches taken in its manufacturing and supply chain operations both in the earlier stages of the pandemic as well as after the first year of the pandemic.FindingsThe COVID-19 pandemic offers a unique risk scenario that is beyond the scope of most existing risk management literature. The impact of the pandemic is very multi-faceted, not location specific but very global and experienced throughout the entire supply chain, across industries and over a much extended timeline with multiple time horizons. In manufacturing operations, there have been major instances of supply chain heroism in the first year of the pandemic and there is a lot more work ahead.Originality/valueThe authors' co-created paper enriches the perspective on COVID-19 research in manufacturing and supply chain operations by pointing at empirical opportunities, the need for more inter disciplinary research and the need to consider multiple time horizons.

JIT Inventory Management Strategy

2019 ◽  
pp. 57-74 ◽  
Author(s):  
Alan D. Smith
Keyword(s):  
Supply Chain ◽  
Inventory Management ◽  
Management Strategy ◽  
Economic Order Quantity ◽  
Just In Time ◽  
Order Quantity ◽  
Business World ◽  
Safety Stock ◽  
Operating Process ◽  
Strategic Approach

Implementing a just-in-time (JIT) inventory management strategy seems to be the latest hot topic in the business world, particularly in manufacturing industries. In today's competitive supply chain environment, more and more companies are either adopting JIT methodology or at least beginning to research and understand how JIT would affect their business. But what exactly is JIT? Many companies may be already putting into practice some of the concepts of JIT – such as looking at always improving or trying to reduce waste in terms of product or labor steps. Some companies may be fully ready to embrace a JIT operating process; yet, perhaps JIT is not the best choice for their business. The goal of this chapter is to develop a better understanding of JIT, from this history behind its inception to the various risks and benefits that relate to adopting JIT from an interdisciplinary/strategic approach to a transdisciplinary viewpoint. Those strategies, which include the basic methods of minimum stock, economic order quantity (EOQ), and Safety stock methods, are explored and explained in this chapter.

‘Green' Supply Chain Management

2018 ◽  
pp. 299-322
Author(s):  
Padmanabha Aital ◽  
Prince Vijai
Keyword(s):  
Resource Allocation ◽  
Supply Chain ◽  
Sustainable Manufacturing ◽  
Green Supply Chain ◽  
Firm Boundaries ◽  
Internal Factors ◽  
Manufacturing Operations ◽  
Operational Practices ◽  
Operational Processes ◽  
Allocation Decisions

Operational practices of ‘green' supply chain processes within as well as across the firm boundaries are strongly linked with the firm performance. However, the desire for such practices is governed by external and/or internal factors. The challenge, therefore, for supply chain and operations managers is to design and develop an operations strategy that ensures the firms investments in such ‘green' initiatives. We develop a theoretical framework for resource allocation strategies for sustainable manufacturing operations that can be characterized as speculative, responsible, efficient, and sustainable resource allocation. This can aid managers in characterizing and controlling the firm's underlying operational processes and guide resource allocation decisions at strategic level.

Evaluating the Use of Electronic Door Seals (E-Seals) on Shipping Containers

2012 ◽  
pp. 283-299
Author(s):  
Edward McCormack ◽  
Mark Jensen ◽  
Al Hovde
Keyword(s):  
Supply Chain ◽  
Cost Effective ◽  
Global Trade ◽  
Shipping Industry ◽  
Mechanical Seals ◽  
Supply Chain Efficiency ◽  
Frequency Standards ◽  
Shipping Containers

In this study, electronic door seals (E-seals) are tested on shipping containers that traveled through ports, over borders, and on roadways. The findings show that using RFID devices increases supply chain efficiency and improves the security of containerized cargo movements, particularly when E-seals replace common mechanical seals. Before the benefits of E-seals can be realized, several barriers must be addressed. A lack of frequency standards for E-seals is a major problem, hindering their acceptability for global trade. Routine use of E-seals also requires new processes that may slow their acceptance by the shipping industry. Disposable E-seals, which decrease industry concerns about costs and enforcement agency concerns about security by eliminating the need to recycle E-seals, are not common because they must be manufactured in large quantities to be cost effective. Compatibility with existing highway systems could also promote E-seal acceptance, as containers could be tracked on roadways.

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