1,721,025 research outputs found
Challenges and opportunities in managing spare parts for durable goods: an empirical study
No full textThe objective of the study is to point out challenges and opportunities in spare parts management practice in durable goods industries, through a case based research carried out in 10 manufacturing companies. The empirical evidence from the cases and the scientific literature, point out challenges and criticalities on three different dimensions: methods (management models and tools); organization (specific spare parts management skills and interfunctional relationships); supply chain perspective (goal setting, information sharing inter-organizational relationships)
Spare parts inventory and demand management. Comparing theoretical approaches with managerial practice.
No full textEvaluation of technical and economic feasibility of additive manufacturing technology: Evidences from a case study
No full text3D Printing has been firstly licensed in the far 1980 year by Charles Hull, the founder and (still) president of 3D Systems, which is a leading company in this sector. The technology has followed an incubation period of almost 25-30 years before becoming enough mature to propose a big spectrum of printing techniques, usable materials which allowed to cross the boundaries of traditional prototyping activities, fully soaking in the direct production of parts, components and final products. The main aim of this work is to test and validate an empirical guideline and tools thanks to which every manufacturing company can evaluate whether additive manufacturing (AM) applications could be suitable according to their specific context. Guidelines and tools, coming from a previous work developed by Pour et al. (2015), have been properly updated and integrated, thanks to a new application in a case study involving a large enterprise, belonging to the textile machinery sector
Servitization of capital good manufacturers: an empirical research in Italian machinery sector
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Improving the distribution planning process in the food&beverage industry: An empirical case study
No full textThe distribution planning process is one of the phases of the broader logistics and production planning process for almost every company, and plays a pivotal role in the overall performances (Lee and Kim, 2002; Bard and Nananukul, 2008). According to Chandra and Fisher (1994), companies can
treat this stage in a dual approach. In the first one the overall planning process is considered as an indivisible entity: according to this way several researchers (Glover et al., 1979; Cohen et al., 1988) proposed models in order to coordinate production and distribution activities. In the second approach, the company considers the distribution policy as an independent stage of the entire planning process (for details, see Thomas and Griffin,
1996). Such an approach is more frequently adopted in industry (Chandra and Fisher, 1994). According to the “independent approach”, this paper
illustrates the results of an empirical study involving a relevant food company operating in Italy. The aim of the study is to investigate the distribution planning process, in order to identify the main parameters that govern it, to analyse their impact on the company’s performances and, finally, to propose some improvements, in terms of costs reduction. According to these objectives, the study addressed, through an intensive case study, two main aspects: (i) the analysis of the company as-is context, encompassing the order process management and the supply chain structure, and (ii) the development of a simulation model that replicates the as-is context and proposes alternative scenarios (to-be), following some ad-hoc optimization rules. Thanks to the simulations, we carried out an optimal configuration for the process parameters, which guarantee, along with the standardization of the order process management, significant economics savings and increased effectiveness for the overall distribution planning process
Improving service parts inventory management for technological products. A simulation-based case study
No full textAnalysis of Servitization in Engineering-To-Order Manufacturing Companies: an Empirical Research
No full textEvidences from OM literature show that in such a context, extending the service business through what has been defined as servitization can lead to generate new and less imitable competitive advantages and new additional revenues and profits. This paper investigate the servitization level of Italian manufacturers that operate in ETO industries-a noteworthy instance of the machinery sector, being Italy the fourth producers of machine tools in the world representing the 7,6% of the worldwide production-and how they support service processes through ICT systems
Optimizing the distribution planning process in supply chains with distribution strategy choice
No full textThis paper studies the optimization of the distribution planning process in a supply chain
composed of set of production plants, a set of regional warehouses and a set of retail customers.
There are several available distribution strategies, based on direct shipping from the
production plants and indirect shipping through the regional warehouses. A mixed integer
linear programming model is formulated to ensure an optimal replenishment of the regional
warehouses and an optimal choice of the distribution strategies to satisfy the demand of
the customers over a certain time horizon. Computational results are obtained in the real
case of a food supply chain of an Italian subsidiary of a German group, encompassing two
production plants located in Germany and two regional warehouses located in Italy, which
deliver 19 products to 200 retail customers located in Italy. We prove that our solutions are
effective and efficiently computed, with an average optimality gap of 4.43% and found using
a time limit of 4min. A comparison is made with an optimized version of the rule of thumb
applied by the company, to provide managerial insights on the choice of the distribution
strategies. Finally, we show that our solution method is effective when it is applied to more
complex logistic networks
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