A DSSBased Framework for Enhancing Collaborative

Authors: Jorge E Hernández Andrew C Lyons Konstantinos Stamatopoulos

Publish Date: 2016/05/02

Volume: 25, Issue: 6, Pages: 1237-1259

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Abstract

The precision engineering sector lies at the heart of the UK’s manufacturing capability Companies that operate in this sector support major economydriving industries such as aerospace defence motorsport nuclear offhighway equipment oil and gas and renewable energy The main companies that constitute this sector are small and mediumsized enterprises SMEs Successful precision engineering businesses are required to master process innovation and supply chain solutions and in these types of business the implementation of innovative collaborative solutions has become a necessary strategy for enhancing SME decisionmaking capability as well as for improving overall business competitiveness The aim of the research described in this paper is to present how by mentoring and supporting SME organisations through online based collaboration it is possible to engage in improved collaborative alliances and how precisionengineering SMEs can benefit and are able to enhance their performance The research is supported by a description of a case study undertaken in a precision engineering SME from the UK northwest region in order to demonstrate the application of the collaborative decision support systems approachNowadays business is undertaken on a global scale and enterprises have to be prepared for intense global competition and for reacting to unexpected changes in the market environment for instance in situations where high demand variability occurs The basis of competition is multifaceted and competitive performance is partially predicated on the quality of the flow of information across enterprises Hence and as established by Ellram and Cooper 1990 supply chains can be regarded as global networks revolving around a core enterprise and its products while facilitating the cash flow information flow and goods flow from purchasing materials to delivering the finished products to the final client Moreover the size of these enterprises will influence the way in which information is treated and how the decisionmaking processes are supported Large companies have a tendency towards medium and longterm relationships For this they utilise robust information technologies to mitigate potential information disruptions in addition to adding value to their processes On the other hand SMEs operate mainly on a shortterm basis and are often dependent on and driven by the requirements of large enterprisesAccording to Axelson 2007 SMEs are the mainstays of the European industrial structure and they are the impeller of contemporary economics Ghose 2001 noted that SMEs contribute the most to any national economy Moreover SMEs play significant roles in the innovation and knowledge transfer of a country Nonetheless SME survival is difficult in these competitive global environments This is partly attributable to the relatively lower labour productivity and profitability of SME’s when compared to large companies Therefore continuously reengineering the business processes and improving the performance of their operations are critical to SMEs Consequently it is necessary to consider efficient agile flexible and reliable solutions in order to tackle the requirements for SMEs particularly for job shop and lowvolume based batch precision engineers It has been stated in the Precision Engineering report Precision Engineering Sector Report 2012 that precisionengineered products constitute a significant proportion of UK exports and the use of technologies in the industry to support the exchange of information is becoming every day more relevant Nevertheless as stated by Ponis and Christou 2013 the use of technologybased decision support systems in SME environments is a rather underexplored research area and presents a relevant research challenge for academic researchers and practitioners Recent studies such as the one from Ramaseshan et al 2015 suggest that a welldefined market strategy and readiness to allocate resources to support the adoption of internetbased technologies are the core factors for successful adoption and implementation of businesstobusiness electronic commerce in SMEs Therefore and under the scope of the C2i ERDF project C2i 2014 the aim of this paper is to present a real application of a webbased solution in a real SME from the UK’s precision engineering sector but and even more important and relevant not from the classical Information’s Technology IT developing point of view but also from the main managerial implications point of view which present a lack on scientific research contribution in this particular field Therefore this paper adds value to the Decision Support System DSS research field This is because it also disclose how these kinds of SME’s can benefit from the use of such IT systems in order to support their individual decisionmaking processes by accessing shared information in a cloudbased environment Within this a conceptual DSSbased framework for the main decisionmaking process is presented with the purpose of theorising the elements of the case study under consideration for the SME production planning decisionmaking Hence the purpose of the webbased solution is to enhancing the customer demand visibility thus to make the SME capable to react to the customer requirementsTherefore the contribution from this paper can be seen from the provision of a clear view about the demonstrable applicability of a wellknown webbased solution in a complex SME which deals with local and international requirements Thus it is highly expected that any SME under this domain can potentially take advantage of this contribution for dealing with the implementation of its own requirements and collaborative solutions but also more important being to realise in advance the expected impacts of such endeavour In this context and in order to achieve such challenging and novel research work in the DSS field this paper at first provides a review for understanding the implications of manufacturing operations management within a collaborative supply chain environment Secondly a holistic and conceptual framework model is introduced for providing the main description of the process and information flows from the SME perspective This is primarily focused on the collaborative production planning process in manufacturing precision engineering industries and explains the main elements selected for addressing the webbased solution Following this and supported by the report from the EMSI 2014 in terms selecting the industry domain the next section presents the case study of one precision engineering SME from the UK northwest region In fact guidelines are provided to articulate the implications of the webbased solution and the online support for the decisionmaking process Following this a discussion about the implications of implementing such webbased solutions in SME’s is provided Finally conclusions and further research are presentedIn this section a literature review is presented to support the proposed model explained in detail in Sect 3 The review method is as follows firstly a review of the scientific literature was undertaken and concerned an analysis of existing approaches that support the development of collaborative operations management processes in supply chains Secondly for the purpose of completing the aforementioned analysis a review is undertaken from the SMEs’ point of view and their role in enhancing the supply chain decisionmaking processAccording to the level of collaboration and the number of participants involved supply chain collaboration can be classified as collaboration among members a value chain and as a supply chain network Poirier 2002 Therefore it is important to consider that collaboration will imply the creation of semantic descriptions that provide a mutual understanding between the firms or nodes that directly or indirectly are wishing to collaborate Chen and Doumeingts 2003 Thus realising that there may be different types of collaboration among the nodes in the supply chain which in turn could belong to different supply chains and also that there could also be different collaborative behaviours models should address each case since the generation of a single model to homogenise collaboration is difficult to manage Poler et al 2008 There are many definitions that can be found for the collaboration concept and in relation to the framework that is addressed in this scientific research contribution the definitions presented by Hernández et al 2011 Hernández et al 2014d stand out as a key support for this purpose These authors consider that collaboration could be defined as the way in which firms belonging to the supply chain will work together to accomplish shared and private objectives by means of the information exchange and the consideration of negotiated decisions In addition to this Cao and Zhang 2011 established that the most important way for supporting the information exchange across supply chains in collaborative environments is by considering that every supply chain node will tend to favour a collaborative relationship This concept was originally defined by Lewieki and Litterer 1985 and establishes that all the participants in a network or at least the vast majority of them will collaborate to become more competitive with regard to other supply chains Sapena et al 2008 suggested the collaboration process can be divided into three sequential states The first relates to interchanging messages or information The second contemplates defining the restrictions associated with the processes and therefore defines the variables with which nodes will assess the results The third and final one considers the ways to model restrictions to obtain model generationbased solutions architectures and tools to support supply chain collaborative policies and mechanisms Moreover with this collaboration terminology the chain could become more competitive in terms of quality costs and times as it would be more efficient Soosay et al 2008 Conversely Chen and Chen 2005 consider that collaborative relationships in the supply chain context will have a positive impact on the integration of the chain’s replenishment processes and its coordination mechanisms This means that the advantages which collaborative relationships offer are related to the profits gained by not only each member of the chain but also by the whole chain Cao and Zhang 2011 Thus there will be a tendency to distribute these profits throughout the chain rather than them being used at a local level by chain members One example of this can be found in the logistics area of distribution where collaborative management in a supply chain will better support the constant modifications made in aspects such as defining objectives distributing raw materials transport planning and requirements to support information interchange The supply chain will tend to be more flexible in terms of physical distributions and will therefore seek to diminish any inefficiency encountered in chain management and planning Kwon et al 2007 According to Reiner and Trcka 2004 and since supplier nodes will be able to identify other suppliers and/or customers’ requirements a supplier must be allowed to communicate downstream and access the supply chain’s requirements and needs to the customer in order to perform a collaborative behaviour across the supply chain networkManthou et al 2004 pointed out that the appropriate use of technologies can help strengthen relationships among supply chain members and will therefore favour integration and collaboration between the various transactions and events present in the different supply chain processes In this way each node could analyse and improve its plans at a local level by considering this external information Dudek and Stadtler 2005 Therefore collaboration in the supply chain will address the joint creation of information interchange processes followed by the implementation of information systems that support these processes Essentially the support of these systems considers the chain’s physical aspects such as the nodes’ geographical distribution as well as data or information aspects such as demand patterns or product characteristics Holweg et al 2005 So from the supply chain collaboration viewpoint it is important to bear in mind that technologies should be able to rapidly and comprehensively respond to customer demand which is generally variable over time Tolone 2000 Hence the use of technologies with algorithmic functionality must be employed to support the changes made in demand patterns One solution to this is presented by Deng et al 2011 who consider using bilevel linear programming to support supply chain management Integrating between technologies and tools to support data analysis and information can help improve decisionmaking processes in supply chains Jiang and Chen 2010 In line with this decisionmaking processes should contemplate the different behaviours of the decision makers in the supply chain manufacturers retailers customers etc to maximise the chain’s profits Cruz 2009

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