Impact of media components from different suppliers on enterokinase productivity in Pichia pastoris

Background The aim of this study was to provide an information about the homogeneity on the level of enterokinase productivity in P. pastoris depending on different suppliers of the media components. Results In previous studies, we performed the optimisation process for the production of enterokinase by improving the fermentation process. Enterokinase is the ideal enzyme for removing fusion partners from target recombinant proteins. In this study, we focused our optimization efforts on the sources of cultivation media components. YPD media components were chosen as variables for these experiments. Several suppliers for particular components were combined and the optimisation procedure was performed in 24-well plates. Peptone had the highest impact on enterokinase production, where the difference between the best and worst results was threefold. The least effect on the production level was recorded for yeast extract with a 1.5 fold difference. The worst combination of media components had a activity of only 0.15 U/ml and the best combination had the activity of 0.88 U/ml, i.e., a 5.87 fold difference. A substantially higher impact on the production level of enterokinase was observed during fermentation in two selected media combinations, where the difference was almost 21-fold. Conclusions Results demonstrated in the present study show that the media components from different suppliers have high impact on enterokinase productivity and also provide the hypothesis that the optimization process should be multidimensional and for achieving best results it is important to perform massive process also in terms of the particular media component supplier .

Leaning Lean: A Case of Reengineering in the Automotive Industry

The scope of this paper focuses on the improvement and reengineering of the die maintenance process for a leading automotive component supplier.

SUPPLIER SELECTION FOR HOUSING DEVELOPMENT BY AN INTEGRATED METHOD WITH INTERVAL ROUGH BOUNDARIES

Residential whole-decoration is an important initiative for housing industrialization in China. Selecting the most suitable component supplier for housing development is of great significance for both property developers and buyers in the implementation of such a strategy. To address such a problem, this study uses hesitant fuzzy linguistic term sets to express the inaccurate judgments of individuals and then introduces a novel probability aggregation approach based on interval rough boundaries to enable a realistic presentation of the collective evaluations of a group. Then, we propose a hybrid multi-expert multiple criteria decision-making model by integrating the Best Worst Method (BWM) and Combined Compromise Solution (CoCoSo) method based on the interval rough boundaries. A case study about the supplier selection for housing development is carried out, which demonstrates the feasibility and applicability of our proposed hybrid model. A comparison study is also performed to further validate the robustness of the model.

Dynamic transportation planning for prefabricated component supply chain

PurposePrefabricated construction concerns off-site production, multi-mode transportation and on-site installation of the prefabricated components, which are interdependent and dynamically interactive, so coordination among the multiple stages along the prefabricated component supply chain (PCSC) is indispensable. This study aims to solve the dynamic transportation planning problem for the PCSC by addressing the interdependency, dynamic interaction and coordination among the multiple stages and different objectives of the stakeholders.Design/methodology/approachThe PCSC is analyzed and then the formulation for the dynamic transportation planning problem is developed based on the just-in-time (JIT) strategy. The particle swarm optimization (PSO) algorithm is applied to solve the dynamic optimization problem.FindingsThe proposed dynamic transportation planning method for the PCSC regarding component supplier selection, transportation planning for means, routes and schedule, site layout planning and transportation plan adjustment is able to facilitate coordination among the multiple stages by addressing their interdependencies and dynamic interactions, as well as different economic objectives of the stakeholders such as suppliers or the contractor.Originality/valueThe study helps to achieve the advantages of prefabricated construction by prompting coordination among multiple stages of the PCSC by realizing different benefits of the stakeholders. In addition, it provides the stakeholders with the competitive bidding prices and the evaluation data for the bids quote. Meanwhile, it contributes to the domain knowledge of the PCSC management with regard to the viewpoint of coordination and integration of multiple stages rather than only one stage as well as the dynamic optimization model based on the JIT strategy and the PSO algorithm.

Multisources Risk Management in a Supply Chain under Option Contracts

Uncertainties in product demand, component yield, and spot price are keys to many industrial settings and they are usually explicitly incorporated. This paper develops an analytical framework to value option contracts in hedging the risks in a supply chain consisting of a component supplier with random yield and a manufacturer facing stochastic demand for end products. The manufacturer can obtain the components from the supplier through firm order contracts and option contracts. Apart from the contract market, there is a spot market in which both the manufacturer and the supplier can buy or sell the components. Analytical expressions for the optimal ordering and production policies are derived. Our study shows that the manufacturer and the supplier can effectively deal with the risks they involve by adopting option contracts. However, we find that the supply chain cannot be coordinated by the traditional option contract. To coordinate such system, we propose a protocol to be combined with the option contract. Finally, the explicit condition for coordination under the proposed contracts is identified.

A Partial Safety Factor Method for System Reliability Prediction With Outsourced Components

System reliability is usually predicted with the assumption that all component states are independent. This assumption may not accurate for systems with outsourced components since their states are strongly dependent and component details may be unknown. The purpose of this study is to develop an accurate system reliability method that can produce complete joint probability density function (PDF) of all the component states, thereby leading to accurate system reliability predictions. The proposed method works for systems whose failures are caused by excessive loading. In addition to the component reliability, system designers also ask for partial safety factors for shared loadings from component suppliers. The information is then sufficient for building a system-level joint PDF. Algorithms are designed for a component supplier to generate partial safety factors. The method enables accurate system reliability predictions without requiring proprietary information from component suppliers.

Accuracy Evaluation of Dense Matching Techniques for Casting Part Dimensional Verification

Product optimization for casting and post-casting manufacturing processes is becoming compulsory to compete in the current global manufacturing scenario. Casting design, simulation and verification tools are becoming crucial for eliminating oversized dimensions without affecting the casting component functionality. Thus, material and production costs decrease to maintain the foundry process profitable on the large-scale component supplier market. New measurement methods, such as dense matching techniques, rely on surface texture of casting parts to enable the 3D dense reconstruction of surface points without the need of an active light source as usually applied with 3D scanning optical sensors. This paper presents the accuracy evaluation of dense matching based approaches for casting part verification. It compares the accuracy obtained by dense matching technique with already certified and validated optical measuring methods. This uncertainty evaluation exercise considers both artificial targets and key natural points to quantify the possibilities and scope of each approximation. Obtained results, for both lab and workshop conditions, show that this image data processing procedure is fit for purpose to fulfill the required measurement tolerances for casting part manufacturing processes.

What Does the Success of Tesla Mean for the Future Dynamics in the Global Automobile Sector?

After reading Jacobides, MacDuffie, and Tae (2016), the success of Tesla in launching a new automobile company in a crowded sector puzzled us. Jacobides, MacDuffie, and Tae (2016) had convinced us that developing the capabilities to become the manufacturer of a complete, safe automobile system would be quite difficult. Since the establishment of the dominant design for the auto in the 1920s, the industry has operated on the premise of massive economies of scale. Original equipment manufacturers’ (OEMs) role in taking responsibility for the legal liability of the whole automobile, combined with their extensive supply and marketing chains, has ensured they remained dominant in the sector despite some missteps with modularisation and outsourcing efforts (Jacobides, MacDuffie, & Tae, 2016; Schulze, MacDuffie, & Taube, 2015). No major component supplier has succeeded in forward integrating into becoming an OEM and no new entrants have challenged the dominance of the incumbent OEMs since the earliest days of the auto industry (Jacobides & MacDuffie, 2013).

A Partial Safety Factor Method for System Reliability Prediction With Outsourced Components

System reliability is usually predicted with the assumption that all component states are independent. This assumption is particularly useful for systems with outsourced components. The assumption, however, may produce large errors in the system reliability prediction since many component states are strongly dependent. The purpose of this study is to develop an accurate system reliability method that can produce complete joint probability density function (PDF) of all the component states, thereby leading to accurate system reliability predictions. The proposed method works for systems whose failures are caused by excessive loading. In addition to the component reliability, system designers also ask for partial safety factors for shared loadings from component suppliers. The information is then sufficient for building a system-level joint PDF. Algorithms are designed for a component supplier to generate partial safety factors, which enables accurate system reliability predictions without requiring proprietary information from component suppliers.