Yousef Amer

Sustainable supply chain for collaborative manufacturing

Purpose – Owing to the manufacturing trend of stringent product disposal regulations, a new business scenario, which requires an alternative disposal option on consumer products and further product recovery operations, is increasingly important for promoting sustainable supply chain performance. The purpose of this paper is to explore the use to post‐use stage of the product lifecycle, that may have significant potential for increasing product utilisation value and reducing product disposal to landfills.Design/methodology/approach – The paper proposes a re‐classification of the 6R (reduce, recover, redesign, reuse, recycle, remanufacturing) methodology for rectifying waste minimisation along a supply chain, to increase product utilisation at the post‐use stage.Findings – Intensive study of 6R considerations to improve end‐of‐life planning and strategy and extend of product lifecycle management is lacking. None of the existing supply chain frameworks clearly illustrates the aspects of 6R perspectives for t...

Optimizing order fulfillment using design for six sigma and fuzzy logic

Abstract Supply chain management aims to add value across the supply chain and customer service is now a major strategic issue. Supply chains are complex and subject to variables of forecast, supply, process, and transportation which can lead to problems such as the bull whip effect, product lateness, damaged goods and stock outs. A key issue facing companies today is how to monitor and control performance across the chain. This paper presents Design for Six Sigma (DFSS), which focuses on customer requirements from the onset, as an effective methodology for monitoring and controlling supply chain variables, optimizing supply chain processes and meeting customer’s requirements. By applying DFSS methodology to the key supply chain process of order fulfillment, a customized representation of detailed activities of order fulfillment processes is demonstrated providing key performance indicators. A theoretical transfer function for predicting the performance of the perfect order incorporating fuzzy set theory provides a way of monitoring supply chain performance.

A systems approach to order fulfilment using design for six sigma methodology

Supply Chain Management (SCM) focuses on a business process approach with an emphasis on having a holistic view of the value chain, customer driven demand and the need to manage successfully both the internal functional and external business process interfaces. In this paper an adaptation of Design for Six Sigma (DFSS) methodology for designing and managing a supply chain is presented, demonstrating how Order fulfilment is one of the major Critical to Customer Requirements (CCRs) for a supply chain. A detailed explanation of the DFSS steps Identify, Design, Optimise and Validate (IDOV) as adapted to supply chain service is illustrated.

Modeling industrial safety: A sociotechnical systems perspective

Highly technological systems such as advanced manufacturing systems, aviation, telecommunications, nuclear power plants, chemical and petroleum process industry are increasingly becoming more complex, leading to new kinds of system failures and accidents. Traditional safety modeling approaches are not suitable to analyze accidents that occur in modern sociotechnical systems, where accident causation is not the result of an individual component failure or human error. This paper discusses some traditional safety models and their limitations, and describes new system-theoretic approaches to the modeling and analysis of accidents in complex systems. This paper also discusses emerging research in cognitive systems engineering, sociological analysis, and resilience engineering for safety analysis, accident modeling and safety management of complex industrial systems.

Implementing design for six sigma to supply chain design

The changing paradigms in manufacturing in the global market since the late 1990s have seen the emergence of more collaborative manufacturing ventures, an increase in outsourcing and a review of the relationship between manufacturing, operations management and logistics and their place in the overall supply chain. Building effective supply chains has become a way to develop a firms competitiveness and profitability requiring firms to make the shift from a functionally based organisation to one focused on business processes, first internally and then across the supply chain members. Consequently supply chain members must have measurable outcomes that reflect bottom line improvement in supply chain processes and research is required to understand how to identify appropriate supply chain metrics, implement them and measure results. Generic supply chain frameworks such as the supply chain operations reference (SCOR) model aim to develop a common supply chain approach for firms with an emphasis on benchmarking but there is some criticism that broader frameworks are required so that managers can link supply chain improvement to strategic plans, key performance indicators and improvement goals. This paper presents design for six sigma (DFSS) as a versatile methodology for approaching supply chain design and performance measurement. The demand management process is described as a critical to customer requirements (CCRs) and its importance to business performance elaborated.

Survey on applications of biased-random key genetic algorithms for solving optimization problems

This paper presents a survey on studies devising biased-random key genetic algorithms (BRKGAs), a novel variant of the ordinary genetic algorithms (GAs) introduced in 2000s, for solving numerous optimization problems up to 2015. The aim is to provide a comprehensive picture of the development of the algorithms and the areas of implementation in literature yet. From the survey, a number of findings include: (1) number of studies tends to increase over the last five years dealing with various combinatorial optimization problems, however limited research deals with continuous variables, (2) local search procedure is the typical hybridization method used to enhance the performance of the algorithms, hence others improvement methods are still potential avenues for future research.

An inventory model of production-inventory policy for food products considering quality loss in raw materials

The majority research on inventory model for deteriorating items in multi-echelon system assumes that a physical depletion of some inventories occurred over time. It means that the inventory is depleted not only due to the demand but also due to some deteriorated items. In food products, however, during a certain period, its quantity remains the same while its quality does degrade over time. Therefore, this study is aimed at developing a more representative inventory model for mimicking food deterioration characteristics. A mathematical model is established to represent the integrated inventory policy of procurement-production-delivery in which the total profit of the whole system is the objective function. The length of the production cycle, the frequency of raw material procurement and finished goods deliveries over the production cycle are the controlling variables. The numerical test indicates that the proposed model yields to a better profit compared to the benchmark model.

An optimisation model for a simultaneous cost-risk reduction in just-in-time systems

Abstract Just-in-time (JIT) is one of lean manufacturing tools, which evokes images of efficiency, minimising unnecessary costs and attractive value for many organisations. However, the risks arising from these benefits have been ignored. These risks impact on system processes disrupting all supply chain parties (suppliers/customers) involved. This research focuses on how the proposed model can simultaneously reduce costs and risks in JIT systems. This model is developed to ascertain an optimal ordering strategy for procuring raw materials, in order to reduce the total cost of the products, and at the same time to reduce the risks arising from this cost reduction within production systems. Also, an example problem is proposed to demonstrate the effectiveness of the developed model. Finally, in comparison between the cost of using the JIT system and the inventory system, the results show the superiority of the use of inventory policy.

Assessing Sustainability in Manufacturing Using a Fuzzy Expert System

One of the recent business challenges is evaluating performance measurement on product returns and recovery operations. Recovery strategy is important in minimising landfill waste. However, there is a lack of measureable criteria to examine the performance attributes of cost, time, waste and quality for a manufactured product with recovery operations in a supply chain. This paper proposes the development of a fuzzy expert system for performance measurement on product returns and recovery operations, which is one of the key supply chain management processes in achieving sustainability in manufacturing. Finally, contributions of this research study are provided.

A Review of Collaborative Manufacturing Network Models

 Abstract—Tough competition in the current global economies has forced manufacturing enterprises, especially small and medium manufacturing enterprises (SMMEs) to collaborate with other companies to survive. They strive to manage their products to achieve a high level of customer satisfaction at a competitive price in a timely manner with the best quality. Collaborative models covering part of the whole production process have been developed providing advantages to the participating companies. Integration of these current collaborative models into a holistic collaborative manufacturing model could provide operational cost savings as well as significantly increasing competitive advantage. However, there is no current review which provides a comprehensive picture of such integration. Therefore, this study aims to provide a thorough literature review of the current collaborative models, their advantages and their collaborative components which are used to support the collaboration process. Four areas of collaborative models namely; collaborative forecasting, collaborative design and product development, collaborative manufacturing and collaborative distribution are discussed. The majority of previous works tend to overlook combinations of collaborative models in the concerned aspects. Hence, future research opportunities to bring those areas more closely linked to each other is proposed so that manufacturing enterprises can take maximum benefit from all of the current models of collaborative manufacturing.