SPONSORED INTERVIEW
stock. This can mean preventing one location from ordering new stock when there is excess stock available in a different part of DB’s own network, for example.
Abouzolof told us: “At the start of the programme, before the move to more optimised inventory planning, every DB store was independent – it bought whatever it wanted. But they moved it more and more into a co-ordinated model. What we’ve deployed for them is more like a network optimisation, where we optimised the entire network rather than specific stock locations.”
Dr Felix Hafner of DB said: “We at DB AG consider it essential to develop an effective and rational inventory management process. We therefore, together with Syncron, developed highly efficient forecasting, replenishment and distribution processes to gain the best possible availability of spare parts and repairable spare parts. We focus on keeping the maintenance of trains (old and new) as efficient and productive as possible, so that constant rail traffic across the whole rail network is guaranteed.”
Global Inventory Management
Syncron’s state-of-the-art solution has its roots in principles developed at the Cranfield Institute of Technology, as it was then called. Abouzolof told us: “The late Professor John Murdoch came up with some ideas on how to optimise inventories and create sophisticated statistical forecasts, and developed an initial solution with PhD students.”
Syncron later bought the rights and developed the solution, initially as a mainframe system, then in client server form in the early 1990s.
More recently, it has been further developed as a Java-based web application, and it is now delivered as ‘software as a service’, with a subscription model rather than users buying physical software.
Abouzolof said: “The principles are more or less the same, although the technology has moved on quite a lot and the system has evolved. Obviously the interface has moved on a lot. There is a very easy-to-use graphical user interface, and although the forecasting techniques used are very advanced,
the
information is presented graphically, using bar charts and 3D graphs for example.”
Forecasting
Deterministic statistical techniques are used when forecasts are being calculated, combining a vast array of data types and information – making it particular important that such data is accurate and collected efficiently. Abouzolof told us: “All of the information is gathered in
one place. In the past, the user would typically have to use multiple systems and multiple screens, with data spread across systems, and the accuracy of the data questionable. It would involve extracting data to a spreadsheet, for example, whereas now, there is a single solution that collects data for the user.
“This comes from lots of different systems, including MRO (maintenance, repair and operations/overhaul) systems, ERP (enterprise resource planning) systems, and internal maintenance planning systems. It gives the user a dashboard where all the information is presented and where a recommendation is given. The user doesn’t need a PhD in statistics to understand the output, and it becomes even easier once they know how to navigate the solution and how the recommendations are provided. The user can accept or reject that recommendation, or modify the parameters, or dive down and see how it was calculated.”
Integrating maintenance data efficiently is particularly important. This includes both deterministic planning – associated with regular maintenance, servicing, overhaul and parts replacement – and planning for ‘unknowns’ such as breakages and sudden unexpected events, which is based on extrapolating from historic statistics and smart planning. Additional factors like scrap rates and demand profiles also have to be taken into account.
Intelligent recommendations
Syncron has invested over the last 20 years to ensure its solution is intelligent and sophisticated, with easy-to-use functionality. Day-to-day calculations and hassle are taken away from the end user, giving them more time to concentrate on the most difficult problems and to think more intelligently. Abouzolof said: “Rather than spending most of their time collecting data from lots of different systems to analyse, the solution takes that away. That saves them time, and allows them to use their time more intelligently. The solution itself is very intelligent and elegant.”
It is sophisticated at spotting demand caused by factors like accidents or weather patterns, he said, even those that have a long-term
impact. “Trying to do that manually can take a lot of time and data-grinding. A person reading spreadsheets cannot necessarily spot those patterns in such an optimised way.”
Syncron’s solution will evaluate all the options and make an order recommendation.
Its system allows the MRO and purchasing processes to be automated, with associated efficiency benefits – as has happened at DB. In the case of scrapped parts for example, supplier orders are automatically created for new products to replace scrapped parts and maintain the rotable parts pool to meet the desired service level.
The system also allows advanced modelling and scenario simulation, for example a change of supplier for a key part. What will be the impacts, lead times, costs and resilience issues associated with a change in supplier from Europe to China, for example, where the price per part may be cheaper but delivery takes months longer? Longer delivery times require more inventory in stock – is it worth it? Simulations and models can help with complex decisions like these.
Performance improvements
Syncron says that within six to twelve months, its solutions yield performance improvements of 20 to 30% in three main areas: customer service levels, supply chain process efficiencies and stock level reductions.
Abouzolof concluded: “It’s important to
emphasise the importance of having accurate data to complement an advanced and optimised inventory management solution. Many companies have not invested in that – we’re finding that again and again.”
Additional information for this article was supplied by Lisa Corbett and Ulrika Olsson.
FOR MORE INFORMATION
T: 0121 503 2654 E:
Lisa.corbett@
syncron.com W:
www.syncron.com
rail technology magazine Aug/Sep 14 | 63
Tony Abouzolof
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116 |
Page 117 |
Page 118 |
Page 119 |
Page 120 |
Page 121 |
Page 122 |
Page 123 |
Page 124 |
Page 125 |
Page 126 |
Page 127 |
Page 128 |
Page 129 |
Page 130 |
Page 131 |
Page 132 |
Page 133 |
Page 134 |
Page 135 |
Page 136 |
Page 137 |
Page 138 |
Page 139 |
Page 140 |
Page 141 |
Page 142 |
Page 143 |
Page 144 |
Page 145 |
Page 146 |
Page 147 |
Page 148 |
Page 149 |
Page 150 |
Page 151 |
Page 152 |
Page 153 |
Page 154 |
Page 155 |
Page 156 |
Page 157 |
Page 158 |
Page 159 |
Page 160 |
Page 161 |
Page 162 |
Page 163 |
Page 164