Success factors in a forming strategic positioning of manufacturing operations within global supply chains

Managing supply chains effectively has become a critical element in enhancing company profitability and has been identified as the new frontier of competitive advantage. An important element of effective supply chain management is the strategic positioning of the company. The strategic positioning process is concerned with the choice of production-centred activities a company carries out internally and those provided externally. Strategic positioning within manufacturing supply chains however is a relatively recent research topic with apparently few articles currently available that explicitly address associated issues directly. Moreover there is no previous research working strategic positioning of manufacturing operations in global context. Therefore the purpose of this paper is to explore strategic positioning within global supply chains. This paper is based on three cases drawn from the cross industry sector manufacturing companies. It describes an exploratory analysis which is aimed at gaining insight into the success factor to form a strategic positioning within global supply chains.

Realising competitive advantage:bicycle manufacture - manufacturing engineering and management

Students at Cranfield Manufacturing Systems Centre helped Brompton Bikes formulate a strategy to meet rapid sales growth. The students took up Operations Excellence MSc, a two-year part-time programme based on the Cranfield MSc in Engineering and Management of Manufacturing Systems, include the Realising Competitive Manufacture module, which is set out to consolidate and embed the knowledge and skills developed throughout the two-year programme. Guided by StratNav process, the students analysed the product families of Brompton, established the basis on which they compete in the market place, and then benchmarked against key competitors. The top five developments identified to be needed by Brompton are: the formation of group technology cells, creation of a robotic brazing facility, and training and recruitment initiatives for production staff.

Key success factors when implementing strategic manufacturing initiatives

Purpose – This paper reports the study of key success factors (KSFs) in the project management of the implementation of strategic manufacturing initiatives (SMIs). Design/methodology/approach – In order to gather the experience and knowledge of many industries, from different geographic locations, in a broad range of types and sizes of SMIs, a questionnaire-based survey of practitioners worldwide was selected as the most appropriate research method among those available. Findings – The identification of those tasks and activities that must be done well in order to succeed in the implementation of a SMI in practice. Practical implications – Practitioners focusing their attention on the KSFs identified are more likely to succeed. Once these factors have been identified, the value of benchmarking project management methodologies then comes from drawing attention to those tasks that are key to the success of the implementation of SMIs. Originality/value – The paper presents new thinking by bringing project management into the operations strategy implementation literature as an important mediating factor for success. In this context the factors that are required for successful implementation are identified.

Towards a theoretical framework for human performance modelling within manufacturing systems design

The performance of direct workers has a significant impact on the competitiveness of many manufacturing systems. Unfortunately, system designers are ill equipped to assess this impact during the design process. An opportunity exists to assist designers by expanding the capabilities of popular simulation modelling tools, and using them as a vehicle to better consider human factors during the process of system design manufacture. To support this requirement, this paper reports on an extensive review of literature that develops a theoretical framework, which summarizes the principal factors and relationships that such a modelling tool should incorporate.

Humans:the missing link in manufacturing simulation?

Computer based discrete event simulation (DES) is one of the most commonly used aids for the design of automotive manufacturing systems. However, DES tools represent machines in extensive detail, while only representing workers as simple resources. This presents a problem when modelling systems with a highly manual work content, such as an assembly line. This paper describes research at Cranfield University, in collaboration with the Ford Motor Company, founded on the assumption that human variation is the cause of a large percentage of the disparity between simulation predictions and real world performance. The research aims to improve the accuracy and reliability of simulation prediction by including models of human factors.

A need to consider human factors during manufacturing system design

Manufacturing systems that are heavily dependent upon direct workers have an inherent complexity that the system designer is often ill-equipped to understand. This complexity is due to the interactions that cause variations in performance of the workers. Variation in human performance can be explained by many factors, however one important factor that is not currently considered in any detail during the design stage is the physical working environment. This paper presents the findings of ongoing research investigating human performance within manufacturing systems. It sets out to identify the form of the relationships that exist between changes in physical working environmental variables and operator performance. These relationships can provide managers with a decision basis when designing and managing manufacturing systems and their environments.

A manufacturing systems modelling using system dynamics:forming a dedicated modelling tool

Discrete event simulation is a popular aid for manufacturing system design; however in application this technique can sometimes be unnecessarily complex. This paper is concerned with applying an alternative technique to manufacturing system design which may well provide an efficient form of rough-cut analysis. This technique is System Dynamics, and the work described in this paper has set about incorporating the principles of this technique into a computer based modelling tool that is tailored to manufacturing system design. This paper is structured to first explore the principles of System Dynamics and how they differ from Discrete Event Simulation. The opportunity for System Dynamics is then explored, and this leads to defining the capabilities that a suitable tool would need. This specification is then transformed into a computer modelling tool, which is then assessed by applying this tool to model an engine production facility. Read More: http://www.worldscientific.com/doi/abs/10.1142/S0219686703000228

Using empirical evidence of variations in worker performance to extend the capabilities of discrete event simulations in manufacturing

Discrete event simulation of manufacturing systems has become widely accepted as an important tool to aid the design of such systems. Often, however, it is applied by practitioners in a manner which largely ignores an important element of industry; namely, the workforce. Workers are usually represented as simple resources, often with deterministic performance values. This approach ignores the potentially large effect that human performance variation can have on a system. A long-term data collection exercise is described with the aim of quantifying the performance variation of workers in a typical automotive assembly plant. The data are presented in a histogram form which is immediately usable in simulations to improve the accuracy of design assessment. The results show levels of skewness and range which are far larger than anticipated by current researchers and practitioners in the field.